While methodology for determining the mode of evolution in coding sequences has been well established,evaluation of adaptation events in emerging types of phenotype data needs further development.Here,we propose an an...While methodology for determining the mode of evolution in coding sequences has been well established,evaluation of adaptation events in emerging types of phenotype data needs further development.Here,we propose an analysis framework(expression variance decomposition,EVaDe)for comparative single-cell expression data based on phenotypic evolution theory.After decomposing the gene expression variance into separate components,we use two strategies to identify genes exhibiting large between-taxon expression divergence and small within-cell-type expression noise in certain cell types,attributing this pattern to putative adaptive evolution.In a dataset of primate prefrontal cortex,we find that such humanspecific key genes enrich with neurodevelopment-related functions,while most other genes exhibit neutral evolution patterns.Specific neuron types are found to harbor more of these key genes than other cell types,thus likely to have experienced more extensive adaptation.Reassuringly,at the molecular sequence level,the key genes are significantly associated with the rapidly evolving conserved non-coding elements.An additional case analysis comparing the naked mole-rat(NMR)with the mouse suggests that innateimmunity-related genes and cell types have undergone putative expression adaptation in NMR.Overall,the EVaDe framework may effectively probe adaptive evolution mode in single-cell expression data.展开更多
Wire-fed laser-arc directed energy deposition(Wire-fed LA-DED)Technol.improves production speed while maintaining high quality and is particularly suited for manufacturing large,complex aluminum or titanium alloy comp...Wire-fed laser-arc directed energy deposition(Wire-fed LA-DED)Technol.improves production speed while maintaining high quality and is particularly suited for manufacturing large,complex aluminum or titanium alloy components.The geometry of the weld bead(height and width)is influenced by multiple intricate parameters and variables during the manufacturing process.Accurately predicting the weld bead shape enables precise control over the surface flatness of the part,helping to prevent defects such as lack of fusion.This significantly reduces dimensional redundancy,enhances printing efficiency,and optimizes material usage.In this study,a quadratic regression prediction model for weld bead geometry was developed using the response surface methodology(RSM),with predictions generated through several machine learning models.These models included the back-propagation neural network(BPNN),support vector regression(SVR),multi-output support vector regression(MOSVR),extreme learning machine(ELM),and a differential evolution-optimized MOSVR(DE-MOSVR)model.Grid search and cross-validation techniques were utilized to identify the optimal parameters for each model to achieve the best predictive performance.A comparison of these models was conducted,followed by an evaluation of their generalization capabilities using an additional 20 sets of test data.The most accurate predictive model was selected based on a comprehensive assessment.The results showed that the DE-MOSVR model outperformed the others,achieving mean squared error,root mean squared error,mean absolute error,and R^(2) values for width(height)predictions of 0.0411(0.0041),0.2028(0.0639),0.1671(0.0550),and 0.9434(0.9433),respectively.It demonstrated the smallest deviation in the validation set,with mean deviations of 1.97% and 1.68%,respectively.The model we developed was validated through the production of prototype parts,providing valuable reference and guidance for predicting and modeling weld bead morphology in the Wire-fed LA-DED process.展开更多
Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its...Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its reactivity.Accurately quantifying the phenolic hydroxyl content in PPO is essential but challenging.In this study,we proposed a method for measuring the phenolic hydroxyl content of PPO using differential UV absorption spectroscopy.In alkaline solutions,the phenolic hydroxyl in PPO completely ionizes to form phenoxide ions,leading to a significant increase in UV absorbance at approximately 250 and 300 nm.Notably,the differential UV absorbance at approximately 300 nm was directly proportional to the phenolic hydroxyl concentration.Using 2,6-dimethylphenol as a standard,a calibration curve was established to relate the phenolic hydroxyl concentration to differential UV absorbance at approximately 300 nm,providing a precise and straightforward method for phenolic hydroxyl quantification in PPO with distinct advantages over conventional techniques.展开更多
Oxygen evolution reaction(OER)is a key step in hydrogen production by water electrolysis technology.How-ever,developing efficient,stable,and low-cost OER electrocatalysts is still challenging.This article presents the...Oxygen evolution reaction(OER)is a key step in hydrogen production by water electrolysis technology.How-ever,developing efficient,stable,and low-cost OER electrocatalysts is still challenging.This article presents the preparation of a series of novel copper iridium nanocatalysts with heterostructures and low iridium content for OER.The electrochemical tests revealed higher OER of Cu@Ir_(0.3) catalyst under acidic conditions with a generated current density of 10 mA/cm^(2) at only 284 mV overpotential.The corresponding OER mass activity was estimated to be 1.057 A/mgIr,a value 8.39-fold higher than that of the commercial IrO_(2).After 50 h of endurance testing,the Cu@Ir_(0.3) catalyst preserved excellent catalytic activity with a negligible rise in overpotential and maintained a good heterostructures.Cu@Ir_(0.3) The excellent OER activity can be attributed to its heterostructure,as con-firmed by density functional theory(DFT)calculations,indicating that Cu@Ir The coupling between isoquanta causes charge redistribution,optimizing the adsorption energy of unsaturated Ir sites for oxygen intermediates and reducing the energy barrier of OER free energy determining the rate step.In summary,this method provides a new approach for designing efficient,stable,and low iridium content OER catalysts.展开更多
In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential r...In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential reasoning(ER)methodology.The proposed approach uses q-RLDFS in order to represent the evaluating values of the alternatives corresponding to the attributes.DE optimization is used to obtain the optimal weights of the attributes,and ER methodology is used to compute the aggregated q-rung linear diophantine fuzzy values(q-RLDFVs)of each alternative.Then the score values of alternatives are computed based on the aggregated q-RLDFVs.An alternative with the maximum score value is selected as a better one.The applicability of the proposed approach has been illustrated in COVID-19 emergency decision-making system and sustainable energy planning management.Moreover,we have validated the proposed approach with a numerical example.Finally,a comparative study is provided with the existing models,where the proposed approach is found to be robust to perform better and consistent in uncertain environments.展开更多
To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID co...To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.展开更多
The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performari...The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performarice comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm （GA）. A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies, indicating that the DE exhibits comparable performance with other algorithms. It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs.展开更多
Some recent research reports that a dendritic neuron model(DNM)can achieve better performance than traditional artificial neuron networks(ANNs)on classification,prediction,and other problems when its parameters are we...Some recent research reports that a dendritic neuron model(DNM)can achieve better performance than traditional artificial neuron networks(ANNs)on classification,prediction,and other problems when its parameters are well-tuned by a learning algorithm.However,the back-propagation algorithm(BP),as a mostly used learning algorithm,intrinsically suffers from defects of slow convergence and easily dropping into local minima.Therefore,more and more research adopts non-BP learning algorithms to train ANNs.In this paper,a dynamic scale-free network-based differential evolution(DSNDE)is developed by considering the demands of convergent speed and the ability to jump out of local minima.The performance of a DSNDE trained DNM is tested on 14 benchmark datasets and a photovoltaic power forecasting problem.Nine meta-heuristic algorithms are applied into comparison,including the champion of the 2017 IEEE Congress on Evolutionary Computation(CEC2017)benchmark competition effective butterfly optimizer with covariance matrix adapted retreat phase(EBOwithCMAR).The experimental results reveal that DSNDE achieves better performance than its peers.展开更多
Sensitivity loop shaping using add-on peak filters is a simple and effective method to reject narrow-band disturbances in hard disk drive （HDD） servo systems. The parallel peak filter is introduced to provide high-g...Sensitivity loop shaping using add-on peak filters is a simple and effective method to reject narrow-band disturbances in hard disk drive （HDD） servo systems. The parallel peak filter is introduced to provide high-gain magnitude in the concerned frequency range of open-loop transfer function. Different from almost all the known peak filters that possess second-order structures, we explore in this paper bow high-order peak filters can be designed to improve the loop shaping performance. The main idea is to replace some of the constant coefficients of common second-order peak filter by frequency-related transfer functions, and then differential evolution （DE） algorithm is adopted to perform optimal design. We creatively introduce chromosome coding and fitness function design, which are original and the key steps that lead to the success of DE applications in control system design. In other words, DE is modified to achieve a novel design for hard disk drive control. Owing to the remarkable searching ability of DE, the expected shape of sensitivity function can be achieved by incorporating the resultant high-order peak filter in parallel with baseline feedback controller. As a result, a seventh-order peak filter is designed to compensate for contact-induced vibration in a high-density HDD servo system, where the benefits of high-order filter are clearly demonstrated.展开更多
For complex systems with high nonlinearity and strong coupling,the decoupling control technology based on proportion integration differentiation(PID)neural network(PIDNN)is used to eliminate the coupling between loops...For complex systems with high nonlinearity and strong coupling,the decoupling control technology based on proportion integration differentiation(PID)neural network(PIDNN)is used to eliminate the coupling between loops.The connection weights of the PIDNN are easy to fall into local optimum due to the use of the gradient descent learning method.In order to solve this problem,a hybrid particle swarm optimization(PSO)and differential evolution(DE)algorithm(PSO-DE)is proposed for optimizing the connection weights of the PIDNN.The DE algorithm is employed as an acceleration operation to help the swarm to get out of local optima traps in case that the optimal result has not been improved after several iterations.Two multivariable controlled plants with strong coupling between input and output pairs are employed to demonstrate the effectiveness of the proposed method.Simulation results show t hat the proposed met hod has better decoupling capabilities and control quality than the previous approaches.展开更多
The differential evolution(DE)algorithm relies mainly on mutation strategy and control parameters'selection.To take full advantage of top elite individuals in terms of fitness and success rates,a new mutation oper...The differential evolution(DE)algorithm relies mainly on mutation strategy and control parameters'selection.To take full advantage of top elite individuals in terms of fitness and success rates,a new mutation operator is proposed.The control parameters such as scale factor and crossover rate are tuned based on their success rates recorded over past evolutionary stages.The proposed DE variant,MIDE,performs the evolution in a piecewise manner,i.e.,after every predefined evolutionary stages,MIDE adjusts its settings to enrich its diversity skills.The performance of the MIDE is validated on two different sets of benchmarks:CEC 2014 and CEC 2017(special sessions&competitions on real-parameter single objective optimization)using different performance measures.In the end,MIDE is also applied to solve constrained engineering problems.The efficiency and effectiveness of the MIDE are further confirmed by a set of experiments.展开更多
Because of their superior problem-solving ability,nature-inspired optimization algorithms are being regularly used in solving complex real-world optimization problems.Engineering academics have recently focused on met...Because of their superior problem-solving ability,nature-inspired optimization algorithms are being regularly used in solving complex real-world optimization problems.Engineering academics have recently focused on meta-heuristic algorithms to solve various optimization challenges.Among the state-of-the-art algorithms,Differential Evolution(DE)is one of the most successful algorithms and is frequently used to solve various industrial problems.Over the previous 2 decades,DE has been heavily modified to improve its capabilities.Several DE variations secured positions in IEEE CEC competitions,establishing their efficacy.However,to our knowledge,there has never been a comparison of performance across various CEC-winning DE versions,which could aid in determining which is the most successful.In this study,the performance of DE and its eight other IEEE CEC competition-winning variants are compared.First,the algorithms have evaluated IEEE CEC 2019 and 2020 bound-constrained functions,and the performances have been compared.One unconstrained problem from IEEE CEC 2011 problem suite and five other constrained mechanical engineering design problems,out of which four issues have been taken from IEEE CEC 2020 non-convex constrained optimization suite,have been solved to compare the performances.Statistical analyses like Friedman's test and Wilcoxon's test are executed to verify the algorithm’s ability statistically.Performance analysis exposes that none of the DE variants can solve all the problems efficiently.Performance of SHADE and ELSHADE-SPACMA are considerable among the methods used for comparison to solve such mechanical design problems.展开更多
Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm ...Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.展开更多
Injection molding machine,hydraulic elevator,speed actuators belong to variable speed pump control cylinder system.Because variable speed pump control cylinder system is a nonlinear hydraulic system,it has some proble...Injection molding machine,hydraulic elevator,speed actuators belong to variable speed pump control cylinder system.Because variable speed pump control cylinder system is a nonlinear hydraulic system,it has some problems such as response lag and poor steady-state accuracy.To solve these problems,for the hydraulic cylinder of injection molding machine driven by the servo motor,a fractional order proportion-integration-diferentiation(FOPID)control strategy is proposed to realize the speed tracking control.Combined with the adaptive differential evolution algorithm,FOPID control strategy is used to determine the parameters of controller on line based on the test on the servo-motor-driven gear-pump-controlled hydraulic cylinder injection molding machine.Then the slef-adaptive differential evolution fractional order PID controller(SADE-FOPID)model of variable speed pump-controlled hydraulic cylinder is established in the test system with simulated loading.The simulation results show that compared with the classical PID control,the FOPID has better steady-state accuracy and fast response when the control parameters are optimized by the adaptive differential evolution algorithm.Experimental results show that SADE-FOPID control strategy is effective and feasible,and has good anti-load disturbance performance.展开更多
Golden eagle optimizer(GEO)is a recently introduced nature-inspired metaheuristic algorithm,which simulates the spiral hunting behavior of golden eagles in nature.Regrettably,the GEO suffers from the challenges of low...Golden eagle optimizer(GEO)is a recently introduced nature-inspired metaheuristic algorithm,which simulates the spiral hunting behavior of golden eagles in nature.Regrettably,the GEO suffers from the challenges of low diversity,slow iteration speed,and stagnation in local optimization when dealing with complicated optimization problems.To ameliorate these deficiencies,an improved hybrid GEO called IGEO,combined with Lévy flight,sine cosine algorithm and differential evolution(DE)strategy,is developed in this paper.The Lévy flight strategy is introduced into the initial stage to increase the diversity of the golden eagle population and make the initial population more abundant;meanwhile,the sine-cosine function can enhance the exploration ability of GEO and decrease the possibility of GEO falling into the local optima.Furthermore,the DE strategy is used in the exploration and exploitation stage to improve accuracy and convergence speed of GEO.Finally,the superiority of the presented IGEO are comprehensively verified by comparing GEO and several state-of-the-art algorithms using(1)the CEC 2017 and CEC 2019 benchmark functions and(2)5 real-world engineering problems respectively.The comparison results demonstrate that the proposed IGEO is a powerful and attractive alternative for solving engineering optimization problems.展开更多
Identifying the geometric information of an object by analyzing the detected radiation fields is an important problem for national and global security.In the present work,an inverse radiation transport model,based on ...Identifying the geometric information of an object by analyzing the detected radiation fields is an important problem for national and global security.In the present work,an inverse radiation transport model,based on the enhanced differential evolution algorithm with global and local neighborhoods(IRT-DEGL),is developed to estimate the unknown layer thickness of the source/shield system with the gamma-ray spectrum.The framework is briefly introduced with the emphasis on handling the enhanced differential evolution algorithm.Using the simulated gamma-ray spectra,the numerical precision of the IRT-DEGL model is evaluated for one-dimensional source systems.Using the detected gamma-ray spectra,the inverse investigations for the unknown thicknesses of multiple shielding layers are performed.By comparing with the traditional gamma-ray absorption method,it is shown that the IRT-EDGL model can provide a much more accurate result and has great potential to be applied for the complicated systems.展开更多
Nowadays, due to increasing population and water shortage and competition for its consumption, especially in the agriculture, which is the largest consumer of water, proper and suitable utilization and optimal use of ...Nowadays, due to increasing population and water shortage and competition for its consumption, especially in the agriculture, which is the largest consumer of water, proper and suitable utilization and optimal use of water resources is essential. One of the important parameters in agriculture field is water distribution network. In this research, differential evolution algorithm (DE) was used to optimize Ismail Abad water supply network. This network is pressurized network and includes 19 pipes and 18 nodes. Optimization of the network has been evaluated by developing an optimization model based on DE algorithm in MATLAB and the dynamic connection with EPANET software for network hydraulic calculation. The developing model was run for the scale factor (F), the crossover constant (Cr), initial population (N) and the number of generations (G) and was identified best adeptness for DE algorithm is 0.6, 0.5, 100 and 200 for F and Cr, N and G, respectively. The optimal solution was compared with the classical empirical method and results showed that implementation cost of the network by DE algorithm was 10.66% lower than the classical empirical method.展开更多
Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler ...Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler metals is ever-increasing.It is of great significance to investigate the optimized composition design methods and to establish systematic design guidelines for brazing filler metals.This study elucidated the fundamental rules for the composition design of brazing filler metals from a three-dimensional perspective encompassing the basic properties of applied brazing filler metals,formability and processability,and overall cost.The basic properties of brazing filler metals refer to their mechanical properties,physicochemical properties,electromagnetic properties,corrosion resistance,and the wettability and fluidity during brazing.The formability and processability of brazing filler metals include the processes of smelting and casting,extrusion,rolling,drawing and ring-making,as well as the processes of granulation,powder production,and the molding of amorphous and microcrystalline structures.The cost of brazing filler metals corresponds to the sum of materials value and manufacturing cost.Improving the comprehensive properties of brazing filler metals requires a comprehensive and systematic consideration of design indicators.Highlighting the unique characteristics of brazing filler metals should focus on relevant technical indicators.Binary or ternary eutectic structures can effectively enhance the flow spreading ability of brazing filler metals,and solid solution structures contribute to the formability.By employing the proposed design guidelines,typical Ag based,Cu based,Zn based brazing filler metals,and Sn based solders were designed and successfully applied in major scientific and engineering projects.展开更多
Binary composites(ZIF-67/rGO)were synthesized by one-step precipitation method using cobalt nitrate hexahydrate as metal source,2-methylimidazole as organic ligand,and reduced graphene oxide(rGO)as carbon carrier.Then...Binary composites(ZIF-67/rGO)were synthesized by one-step precipitation method using cobalt nitrate hexahydrate as metal source,2-methylimidazole as organic ligand,and reduced graphene oxide(rGO)as carbon carrier.Then Ru3+was introduced for ion exchange,and the porous Ru-doped Co_(3)O_(4)/rGO(Ru-Co_(3)O_(4)/rGO)composite electrocatalyst was prepared by annealing.The phase structure,morphology,and valence state of the catalyst were analyzed by X-ray powder diffraction(XRD),scanning electron microscope(SEM),transmission electron microscopy(TEM),and X-ray photoelectron spectroscopy(XPS).In 1 mol·L^(-1)KOH,the oxygen evolution reaction(OER)performance of the catalyst was measured by linear sweep voltammetry,cyclic voltammetry,and chronoamperometry.The results show that the combination of Ru doping and rGO provides a fast channel for collaborative electron transfer.At the same time,rGO as a carbon carrier can improve the electrical conductivity of Ru-Co_(3)O_(4)particles,and the uniformly dispersed nanoparticles enable the reactants to diffuse freely on the catalyst.The results showed that the electrochemical performance of Ru-Co_(3)O_(4)/rGO was much better than that of Co_(3)O_(4)/rGO,and the overpotential of Ru-Co_(3)O_(4)/rGO was 363.5 mV at the current density of 50 mA·cm^(-2).展开更多
Sulfur-doped iron-cobalt tannate nanorods(S-FeCoTA)derived from metal-organic frameworks(MOFs)as electrocatalysts were synthesized via a one-step hydrothermal method.The optimized S-FeCoTA was interlaced by loose nano...Sulfur-doped iron-cobalt tannate nanorods(S-FeCoTA)derived from metal-organic frameworks(MOFs)as electrocatalysts were synthesized via a one-step hydrothermal method.The optimized S-FeCoTA was interlaced by loose nanorods,which had many voids.The S-FeCoTA catalysts exhibited excellent electrochemical oxygen evolution reaction(OER)performance with a low overpotential of 273 mV at 10 mA·cm^(-2)and a small Tafel slope of 36 mV·dec^(-1)in 1 mol·L^(-1)KOH.The potential remained at 1.48 V(vs RHE)at 10 mA·cm^(-2)under continuous testing for 15 h,implying that S-FeCoTA had good stability.The Faraday efficiency of S-FeCoTA was 94%.The outstanding OER activity of S-FeCoTA is attributed to the synergistic effects among S,Fe,and Co,thus promoting electron transfer,reducing the reaction kinetic barrier,and enhancing the OER performance.展开更多
文摘While methodology for determining the mode of evolution in coding sequences has been well established,evaluation of adaptation events in emerging types of phenotype data needs further development.Here,we propose an analysis framework(expression variance decomposition,EVaDe)for comparative single-cell expression data based on phenotypic evolution theory.After decomposing the gene expression variance into separate components,we use two strategies to identify genes exhibiting large between-taxon expression divergence and small within-cell-type expression noise in certain cell types,attributing this pattern to putative adaptive evolution.In a dataset of primate prefrontal cortex,we find that such humanspecific key genes enrich with neurodevelopment-related functions,while most other genes exhibit neutral evolution patterns.Specific neuron types are found to harbor more of these key genes than other cell types,thus likely to have experienced more extensive adaptation.Reassuringly,at the molecular sequence level,the key genes are significantly associated with the rapidly evolving conserved non-coding elements.An additional case analysis comparing the naked mole-rat(NMR)with the mouse suggests that innateimmunity-related genes and cell types have undergone putative expression adaptation in NMR.Overall,the EVaDe framework may effectively probe adaptive evolution mode in single-cell expression data.
基金supported by Natural Science Foundation of Shandong Province(Grant No.ZR202212010161)Natural Science Foundation of Qingdao(Grant No.23-2-1-83-zyyd-jch)+1 种基金Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515110116)the National Natural Science Foundation of China(Grant No.52405359).
文摘Wire-fed laser-arc directed energy deposition(Wire-fed LA-DED)Technol.improves production speed while maintaining high quality and is particularly suited for manufacturing large,complex aluminum or titanium alloy components.The geometry of the weld bead(height and width)is influenced by multiple intricate parameters and variables during the manufacturing process.Accurately predicting the weld bead shape enables precise control over the surface flatness of the part,helping to prevent defects such as lack of fusion.This significantly reduces dimensional redundancy,enhances printing efficiency,and optimizes material usage.In this study,a quadratic regression prediction model for weld bead geometry was developed using the response surface methodology(RSM),with predictions generated through several machine learning models.These models included the back-propagation neural network(BPNN),support vector regression(SVR),multi-output support vector regression(MOSVR),extreme learning machine(ELM),and a differential evolution-optimized MOSVR(DE-MOSVR)model.Grid search and cross-validation techniques were utilized to identify the optimal parameters for each model to achieve the best predictive performance.A comparison of these models was conducted,followed by an evaluation of their generalization capabilities using an additional 20 sets of test data.The most accurate predictive model was selected based on a comprehensive assessment.The results showed that the DE-MOSVR model outperformed the others,achieving mean squared error,root mean squared error,mean absolute error,and R^(2) values for width(height)predictions of 0.0411(0.0041),0.2028(0.0639),0.1671(0.0550),and 0.9434(0.9433),respectively.It demonstrated the smallest deviation in the validation set,with mean deviations of 1.97% and 1.68%,respectively.The model we developed was validated through the production of prototype parts,providing valuable reference and guidance for predicting and modeling weld bead morphology in the Wire-fed LA-DED process.
基金the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01072)the Institute of Zhejiang University-Quzhou for their financial support。
文摘Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its reactivity.Accurately quantifying the phenolic hydroxyl content in PPO is essential but challenging.In this study,we proposed a method for measuring the phenolic hydroxyl content of PPO using differential UV absorption spectroscopy.In alkaline solutions,the phenolic hydroxyl in PPO completely ionizes to form phenoxide ions,leading to a significant increase in UV absorbance at approximately 250 and 300 nm.Notably,the differential UV absorbance at approximately 300 nm was directly proportional to the phenolic hydroxyl concentration.Using 2,6-dimethylphenol as a standard,a calibration curve was established to relate the phenolic hydroxyl concentration to differential UV absorbance at approximately 300 nm,providing a precise and straightforward method for phenolic hydroxyl quantification in PPO with distinct advantages over conventional techniques.
基金supported by the Major Science and Technology Special Plan of Yunnan Province(Nos.202302AB080012 and 202402AB080004)the National Natural Science Foundation of China(No.22264025)+1 种基金the Basic Research Foundation of Yunnan Province(Nos.202401AS070033 and 202501AT070055)the Reserve talents for young and middleaged academic and technical leaders project of Yunnan Province(No.202405AC350071).
文摘Oxygen evolution reaction(OER)is a key step in hydrogen production by water electrolysis technology.How-ever,developing efficient,stable,and low-cost OER electrocatalysts is still challenging.This article presents the preparation of a series of novel copper iridium nanocatalysts with heterostructures and low iridium content for OER.The electrochemical tests revealed higher OER of Cu@Ir_(0.3) catalyst under acidic conditions with a generated current density of 10 mA/cm^(2) at only 284 mV overpotential.The corresponding OER mass activity was estimated to be 1.057 A/mgIr,a value 8.39-fold higher than that of the commercial IrO_(2).After 50 h of endurance testing,the Cu@Ir_(0.3) catalyst preserved excellent catalytic activity with a negligible rise in overpotential and maintained a good heterostructures.Cu@Ir_(0.3) The excellent OER activity can be attributed to its heterostructure,as con-firmed by density functional theory(DFT)calculations,indicating that Cu@Ir The coupling between isoquanta causes charge redistribution,optimizing the adsorption energy of unsaturated Ir sites for oxygen intermediates and reducing the energy barrier of OER free energy determining the rate step.In summary,this method provides a new approach for designing efficient,stable,and low iridium content OER catalysts.
文摘In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential reasoning(ER)methodology.The proposed approach uses q-RLDFS in order to represent the evaluating values of the alternatives corresponding to the attributes.DE optimization is used to obtain the optimal weights of the attributes,and ER methodology is used to compute the aggregated q-rung linear diophantine fuzzy values(q-RLDFVs)of each alternative.Then the score values of alternatives are computed based on the aggregated q-RLDFVs.An alternative with the maximum score value is selected as a better one.The applicability of the proposed approach has been illustrated in COVID-19 emergency decision-making system and sustainable energy planning management.Moreover,we have validated the proposed approach with a numerical example.Finally,a comparative study is provided with the existing models,where the proposed approach is found to be robust to perform better and consistent in uncertain environments.
基金the National Natural Science Foundation of China (60375001)the Scientific Research Foundation of Hunan Provincial Education Department (05B016).
文摘To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.
基金Project (No. 2008AA06A413) supported by the National High-Tech R&D (863) Program of China
文摘The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performarice comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm （GA）. A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies, indicating that the DE exhibits comparable performance with other algorithms. It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs.
基金This work was partially supported by the National Natural Science Foundation of China(62073173,61833011)the Natural Science Foundation of Jiangsu Province,China(BK20191376)the Nanjing University of Posts and Telecommunications(NY220193,NY220145)。
文摘Some recent research reports that a dendritic neuron model(DNM)can achieve better performance than traditional artificial neuron networks(ANNs)on classification,prediction,and other problems when its parameters are well-tuned by a learning algorithm.However,the back-propagation algorithm(BP),as a mostly used learning algorithm,intrinsically suffers from defects of slow convergence and easily dropping into local minima.Therefore,more and more research adopts non-BP learning algorithms to train ANNs.In this paper,a dynamic scale-free network-based differential evolution(DSNDE)is developed by considering the demands of convergent speed and the ability to jump out of local minima.The performance of a DSNDE trained DNM is tested on 14 benchmark datasets and a photovoltaic power forecasting problem.Nine meta-heuristic algorithms are applied into comparison,including the champion of the 2017 IEEE Congress on Evolutionary Computation(CEC2017)benchmark competition effective butterfly optimizer with covariance matrix adapted retreat phase(EBOwithCMAR).The experimental results reveal that DSNDE achieves better performance than its peers.
基金supported by National Natural Science Foundation of China(Nos.61640310 and 61433011)
文摘Sensitivity loop shaping using add-on peak filters is a simple and effective method to reject narrow-band disturbances in hard disk drive （HDD） servo systems. The parallel peak filter is introduced to provide high-gain magnitude in the concerned frequency range of open-loop transfer function. Different from almost all the known peak filters that possess second-order structures, we explore in this paper bow high-order peak filters can be designed to improve the loop shaping performance. The main idea is to replace some of the constant coefficients of common second-order peak filter by frequency-related transfer functions, and then differential evolution （DE） algorithm is adopted to perform optimal design. We creatively introduce chromosome coding and fitness function design, which are original and the key steps that lead to the success of DE applications in control system design. In other words, DE is modified to achieve a novel design for hard disk drive control. Owing to the remarkable searching ability of DE, the expected shape of sensitivity function can be achieved by incorporating the resultant high-order peak filter in parallel with baseline feedback controller. As a result, a seventh-order peak filter is designed to compensate for contact-induced vibration in a high-density HDD servo system, where the benefits of high-order filter are clearly demonstrated.
基金This work was supported by the Key Project of Chinese Ministry of Education(No.212135)the Guangxi Natural Science Foundation(No.2012GXNSFBA053165)+1 种基金the Projec t of Education Department of Guangxi(No.201203YB131)the Project of Guangxi Key Laboratory(No.14-045-44)。
文摘For complex systems with high nonlinearity and strong coupling,the decoupling control technology based on proportion integration differentiation(PID)neural network(PIDNN)is used to eliminate the coupling between loops.The connection weights of the PIDNN are easy to fall into local optimum due to the use of the gradient descent learning method.In order to solve this problem,a hybrid particle swarm optimization(PSO)and differential evolution(DE)algorithm(PSO-DE)is proposed for optimizing the connection weights of the PIDNN.The DE algorithm is employed as an acceleration operation to help the swarm to get out of local optima traps in case that the optimal result has not been improved after several iterations.Two multivariable controlled plants with strong coupling between input and output pairs are employed to demonstrate the effectiveness of the proposed method.Simulation results show t hat the proposed met hod has better decoupling capabilities and control quality than the previous approaches.
基金supported by the A*STAR under its RIE2020 Advanced Manufacturing and Engineering(AME)Industry Alignment Fund-Pre-Positioning(IAF-PP)(Award A19D6a0053)the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP22H03643)。
文摘The differential evolution(DE)algorithm relies mainly on mutation strategy and control parameters'selection.To take full advantage of top elite individuals in terms of fitness and success rates,a new mutation operator is proposed.The control parameters such as scale factor and crossover rate are tuned based on their success rates recorded over past evolutionary stages.The proposed DE variant,MIDE,performs the evolution in a piecewise manner,i.e.,after every predefined evolutionary stages,MIDE adjusts its settings to enrich its diversity skills.The performance of the MIDE is validated on two different sets of benchmarks:CEC 2014 and CEC 2017(special sessions&competitions on real-parameter single objective optimization)using different performance measures.In the end,MIDE is also applied to solve constrained engineering problems.The efficiency and effectiveness of the MIDE are further confirmed by a set of experiments.
文摘Because of their superior problem-solving ability,nature-inspired optimization algorithms are being regularly used in solving complex real-world optimization problems.Engineering academics have recently focused on meta-heuristic algorithms to solve various optimization challenges.Among the state-of-the-art algorithms,Differential Evolution(DE)is one of the most successful algorithms and is frequently used to solve various industrial problems.Over the previous 2 decades,DE has been heavily modified to improve its capabilities.Several DE variations secured positions in IEEE CEC competitions,establishing their efficacy.However,to our knowledge,there has never been a comparison of performance across various CEC-winning DE versions,which could aid in determining which is the most successful.In this study,the performance of DE and its eight other IEEE CEC competition-winning variants are compared.First,the algorithms have evaluated IEEE CEC 2019 and 2020 bound-constrained functions,and the performances have been compared.One unconstrained problem from IEEE CEC 2011 problem suite and five other constrained mechanical engineering design problems,out of which four issues have been taken from IEEE CEC 2020 non-convex constrained optimization suite,have been solved to compare the performances.Statistical analyses like Friedman's test and Wilcoxon's test are executed to verify the algorithm’s ability statistically.Performance analysis exposes that none of the DE variants can solve all the problems efficiently.Performance of SHADE and ELSHADE-SPACMA are considerable among the methods used for comparison to solve such mechanical design problems.
文摘Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.
基金National Natural Science Foundation of China(No.51675399)。
文摘Injection molding machine,hydraulic elevator,speed actuators belong to variable speed pump control cylinder system.Because variable speed pump control cylinder system is a nonlinear hydraulic system,it has some problems such as response lag and poor steady-state accuracy.To solve these problems,for the hydraulic cylinder of injection molding machine driven by the servo motor,a fractional order proportion-integration-diferentiation(FOPID)control strategy is proposed to realize the speed tracking control.Combined with the adaptive differential evolution algorithm,FOPID control strategy is used to determine the parameters of controller on line based on the test on the servo-motor-driven gear-pump-controlled hydraulic cylinder injection molding machine.Then the slef-adaptive differential evolution fractional order PID controller(SADE-FOPID)model of variable speed pump-controlled hydraulic cylinder is established in the test system with simulated loading.The simulation results show that compared with the classical PID control,the FOPID has better steady-state accuracy and fast response when the control parameters are optimized by the adaptive differential evolution algorithm.Experimental results show that SADE-FOPID control strategy is effective and feasible,and has good anti-load disturbance performance.
基金National Natural Science Foundation of China(Grant No.51875454).
文摘Golden eagle optimizer(GEO)is a recently introduced nature-inspired metaheuristic algorithm,which simulates the spiral hunting behavior of golden eagles in nature.Regrettably,the GEO suffers from the challenges of low diversity,slow iteration speed,and stagnation in local optimization when dealing with complicated optimization problems.To ameliorate these deficiencies,an improved hybrid GEO called IGEO,combined with Lévy flight,sine cosine algorithm and differential evolution(DE)strategy,is developed in this paper.The Lévy flight strategy is introduced into the initial stage to increase the diversity of the golden eagle population and make the initial population more abundant;meanwhile,the sine-cosine function can enhance the exploration ability of GEO and decrease the possibility of GEO falling into the local optima.Furthermore,the DE strategy is used in the exploration and exploitation stage to improve accuracy and convergence speed of GEO.Finally,the superiority of the presented IGEO are comprehensively verified by comparing GEO and several state-of-the-art algorithms using(1)the CEC 2017 and CEC 2019 benchmark functions and(2)5 real-world engineering problems respectively.The comparison results demonstrate that the proposed IGEO is a powerful and attractive alternative for solving engineering optimization problems.
基金supported by the CAEP foundation for Development of Science and Technology(No.2015B0103014)National Natural Science Foundation of China(No.11605163)
文摘Identifying the geometric information of an object by analyzing the detected radiation fields is an important problem for national and global security.In the present work,an inverse radiation transport model,based on the enhanced differential evolution algorithm with global and local neighborhoods(IRT-DEGL),is developed to estimate the unknown layer thickness of the source/shield system with the gamma-ray spectrum.The framework is briefly introduced with the emphasis on handling the enhanced differential evolution algorithm.Using the simulated gamma-ray spectra,the numerical precision of the IRT-DEGL model is evaluated for one-dimensional source systems.Using the detected gamma-ray spectra,the inverse investigations for the unknown thicknesses of multiple shielding layers are performed.By comparing with the traditional gamma-ray absorption method,it is shown that the IRT-EDGL model can provide a much more accurate result and has great potential to be applied for the complicated systems.
文摘Nowadays, due to increasing population and water shortage and competition for its consumption, especially in the agriculture, which is the largest consumer of water, proper and suitable utilization and optimal use of water resources is essential. One of the important parameters in agriculture field is water distribution network. In this research, differential evolution algorithm (DE) was used to optimize Ismail Abad water supply network. This network is pressurized network and includes 19 pipes and 18 nodes. Optimization of the network has been evaluated by developing an optimization model based on DE algorithm in MATLAB and the dynamic connection with EPANET software for network hydraulic calculation. The developing model was run for the scale factor (F), the crossover constant (Cr), initial population (N) and the number of generations (G) and was identified best adeptness for DE algorithm is 0.6, 0.5, 100 and 200 for F and Cr, N and G, respectively. The optimal solution was compared with the classical empirical method and results showed that implementation cost of the network by DE algorithm was 10.66% lower than the classical empirical method.
基金National Natural Science Foundation of China(U22A20191)。
文摘Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler metals is ever-increasing.It is of great significance to investigate the optimized composition design methods and to establish systematic design guidelines for brazing filler metals.This study elucidated the fundamental rules for the composition design of brazing filler metals from a three-dimensional perspective encompassing the basic properties of applied brazing filler metals,formability and processability,and overall cost.The basic properties of brazing filler metals refer to their mechanical properties,physicochemical properties,electromagnetic properties,corrosion resistance,and the wettability and fluidity during brazing.The formability and processability of brazing filler metals include the processes of smelting and casting,extrusion,rolling,drawing and ring-making,as well as the processes of granulation,powder production,and the molding of amorphous and microcrystalline structures.The cost of brazing filler metals corresponds to the sum of materials value and manufacturing cost.Improving the comprehensive properties of brazing filler metals requires a comprehensive and systematic consideration of design indicators.Highlighting the unique characteristics of brazing filler metals should focus on relevant technical indicators.Binary or ternary eutectic structures can effectively enhance the flow spreading ability of brazing filler metals,and solid solution structures contribute to the formability.By employing the proposed design guidelines,typical Ag based,Cu based,Zn based brazing filler metals,and Sn based solders were designed and successfully applied in major scientific and engineering projects.
文摘Binary composites(ZIF-67/rGO)were synthesized by one-step precipitation method using cobalt nitrate hexahydrate as metal source,2-methylimidazole as organic ligand,and reduced graphene oxide(rGO)as carbon carrier.Then Ru3+was introduced for ion exchange,and the porous Ru-doped Co_(3)O_(4)/rGO(Ru-Co_(3)O_(4)/rGO)composite electrocatalyst was prepared by annealing.The phase structure,morphology,and valence state of the catalyst were analyzed by X-ray powder diffraction(XRD),scanning electron microscope(SEM),transmission electron microscopy(TEM),and X-ray photoelectron spectroscopy(XPS).In 1 mol·L^(-1)KOH,the oxygen evolution reaction(OER)performance of the catalyst was measured by linear sweep voltammetry,cyclic voltammetry,and chronoamperometry.The results show that the combination of Ru doping and rGO provides a fast channel for collaborative electron transfer.At the same time,rGO as a carbon carrier can improve the electrical conductivity of Ru-Co_(3)O_(4)particles,and the uniformly dispersed nanoparticles enable the reactants to diffuse freely on the catalyst.The results showed that the electrochemical performance of Ru-Co_(3)O_(4)/rGO was much better than that of Co_(3)O_(4)/rGO,and the overpotential of Ru-Co_(3)O_(4)/rGO was 363.5 mV at the current density of 50 mA·cm^(-2).
文摘Sulfur-doped iron-cobalt tannate nanorods(S-FeCoTA)derived from metal-organic frameworks(MOFs)as electrocatalysts were synthesized via a one-step hydrothermal method.The optimized S-FeCoTA was interlaced by loose nanorods,which had many voids.The S-FeCoTA catalysts exhibited excellent electrochemical oxygen evolution reaction(OER)performance with a low overpotential of 273 mV at 10 mA·cm^(-2)and a small Tafel slope of 36 mV·dec^(-1)in 1 mol·L^(-1)KOH.The potential remained at 1.48 V(vs RHE)at 10 mA·cm^(-2)under continuous testing for 15 h,implying that S-FeCoTA had good stability.The Faraday efficiency of S-FeCoTA was 94%.The outstanding OER activity of S-FeCoTA is attributed to the synergistic effects among S,Fe,and Co,thus promoting electron transfer,reducing the reaction kinetic barrier,and enhancing the OER performance.
