The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a pati...The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD...In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.展开更多
On-machine measurement(OMM)stands out as a pivotal technology in complex curved surface adaptive machining.However,the complex structure inherent in workpieces poses a significant challenge as the stylus orientation f...On-machine measurement(OMM)stands out as a pivotal technology in complex curved surface adaptive machining.However,the complex structure inherent in workpieces poses a significant challenge as the stylus orientation frequently shifts during the measurement process.Consequently,a substantial amount of time is allocated to calibrating pre-travel error and probe movement.Furthermore,the frequent movement of machine tools also increases the influence of machine errors.To enhance both accuracy and efficiency,an optimization strategy for the OMM process is proposed.Based on the kinematic chain of the machine tools,the relationship between the angle combination of rotary axes,the stylus orientation,and the calibration position of pre-travel error is disclosed.Additionally,an OMM efficiency optimization model for complex curved surfaces is developed.This model is solved to produce the optimal efficiency angle combinations for each to-be-measured point.Within each angle combination,the effects of positioning errors on measurement results are addressed by coordinate system offset and measurement result compensation method.Finally,the experiments on an impeller are used to demonstrate the practical utility of the proposed method.展开更多
In tunnel construction,tunnel boring machine(TBM)tunnelling typically relies on manual experience with sub-optimal control parameters,which can easily lead to inefficiency and high costs.This study proposed an intelli...In tunnel construction,tunnel boring machine(TBM)tunnelling typically relies on manual experience with sub-optimal control parameters,which can easily lead to inefficiency and high costs.This study proposed an intelligent decision-making method for TBM tunnelling control parameters based on multiobjective optimization(MOO).First,the effective TBM operation dataset is obtained through data preprocessing of the Songhua River(YS)tunnel project in China.Next,the proposed method begins with developing machine learning models for predicting TBM tunnelling performance parameters(i.e.total thrust and cutterhead torque),rock mass classification,and hazard risks(i.e.tunnel collapse and shield jamming).Then,considering three optimal objectives,(i.e.,penetration rate,rock-breaking energy consumption,and cutterhead hob wear),the MOO framework and corresponding mathematical expression are established.The Pareto optimal front is solved using DE-NSGA-II algorithm.Finally,the optimal control parameters(i.e.,advance rate and cutterhead rotation speed)are obtained by the satisfactory solution determination criterion,which can balance construction safety and efficiency with satisfaction.Furthermore,the proposed method is validated through 50 cases of TBM tunnelling,showing promising potential of application.展开更多
Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm opt...Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.展开更多
Reinforcement learning(RL)has been widely studied as an efficient class of machine learning methods for adaptive optimal control under uncertainties.In recent years,the applications of RL in optimised decision-making ...Reinforcement learning(RL)has been widely studied as an efficient class of machine learning methods for adaptive optimal control under uncertainties.In recent years,the applications of RL in optimised decision-making and motion control of intelligent vehicles have received increasing attention.Due to the complex and dynamic operating environments of intelligent vehicles,it is necessary to improve the learning efficiency and generalisation ability of RL-based decision and control algorithms under different conditions.This survey systematically examines the theoretical foundations,algorithmic advancements and practical challenges of applying RL to intelligent vehicle systems operating in complex and dynamic environments.The major algorithm frameworks of RL are first introduced,and the recent advances in RL-based decision-making and control of intelligent vehicles are overviewed.In addition to self-learning decision and control approaches using state measurements,the developments of DRL methods for end-to-end driving control of intelligent vehicles are summarised.The open problems and directions for further research works are also discussed.展开更多
This study was conducted to investigate the flow field characteristics of right-angled flow passage with various cavities in the typical hydraulic manifold block.A low-speed visualization test rig was developed and th...This study was conducted to investigate the flow field characteristics of right-angled flow passage with various cavities in the typical hydraulic manifold block.A low-speed visualization test rig was developed and the flow field of the right-angled flow passage with different cavity structures was measured using 2D-PIV technique.Numerical model was established to simulate the three-dimensional flow field.Seven eddy viscosity turbulence models were investigated in predicting the flow field by comparing against the particle image relocimetry(PIV)measurement results.By defining the weight error function K,the S-A model was selected as the appropriate turbulence model.Then,a three-factor,three-level response surface numerical test was conducted to investigate the influence of flow passage connection type,cavity diameter and cavity length-diameter ratio on pressure loss.The results show that the Box-Benhnken Design(BBD)model can predict the total pressure loss accurately.The optimal factor level appeared in flow passage connection type II,14.64 mm diameter and 67.53%cavity length-diameter ratio.The total pressure loss decreased by 11.15%relative to the worst factor level,and total pressure loss can be reduced by 64.75%when using an arc transition right-angled flow passage,which indicates a new direction for the optimization design of flow passage in hydraulic manifold blocks.展开更多
An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main f...An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.展开更多
The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,mo...The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively.展开更多
Optimization of fracturing perforation is of great importance to the commingling gas production in coal measure strata.In this paper,a 3 D lattice algorithm hydraulic fracturing simulator was employed to study the eff...Optimization of fracturing perforation is of great importance to the commingling gas production in coal measure strata.In this paper,a 3 D lattice algorithm hydraulic fracturing simulator was employed to study the effects of perforation position and length on hydraulic fracture propagation in coal measures of the Lin-Xing block,China.Based on field data,three lithologic combinations are simulated:1)a thick section of coal seam sandwiched by sandstones;2)a thin coal seam layer overlay by gas-bearing tight sandstone;3)two coal seams separated by a thin layer of sandstone.Our simulation shows that perforation position and length in multi-layer reservoirs play a major role in hydraulic fracture propagation.Achieving maximum stimulated volume requires consideration of lithologic sequence,coal seam thickness,stress states,and rock properties.To improve the combined gas production in coal measure strata,it is possible to simultaneously stimulate multiple coal seams or adjacent gas-bearing sandstones.In these cases,perforation location and length also significantly impact fracture propagation,and therefore should be carefully designed.Our simulation results using 3 D lattice algorithm are qualitatively consistent with laboratory physical simulation.3 D lattice models can be used to effectively simulate the fracture propagation through layers in coal measure strata.The numerical results provide guidance for perforation optimization in the hydraulic fracturing of coal measure strata.展开更多
A lifetime prediction method for high-reliability tantalum （Ta） capacitors was proposed, based on multiple degradation measures and grey model （GM）. For analyzing performance degradation data, a two-parameter mode...A lifetime prediction method for high-reliability tantalum （Ta） capacitors was proposed, based on multiple degradation measures and grey model （GM）. For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization （PSO） was used. Then, the new PSO-GM（1, 2, co） optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.展开更多
D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure.Ho...D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure.However,the mass assignments given by unknown information sources are disordered.How to measure the difference between the mass assignments has aroused people’s interest.In this paper,inspired by the information volume,a novel distance-based measure is proposed to measure the difference between mass assignments.The method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass assignments.At the same time,it is verified that the measure not only meets the properties of distance,but also proves the superiority of the proposed Information Volume Distance(IVD)through simulation experiments.Meanwhile,in the process of information fusion,the reliability of each source could be quantified through IVD.Therefore,based on IVD,a new multi-source information algorithm is proposed to solve the problem of multi-source information fusion.Moreover,algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness.展开更多
A new method of phase measurement based on optimization is presented. Simulations were ran with synthesized signals, and comparison was made with some spectral domain methods. The results show that, with a suitable n...A new method of phase measurement based on optimization is presented. Simulations were ran with synthesized signals, and comparison was made with some spectral domain methods. The results show that, with a suitable number of samples processed, this method is superior to other methods in terms of accuracy, while the amplitude and phase of distortion component have no effect on accuracy.展开更多
In comparison to the construction of modern highway engineering,several of China’s early pavement construction concerns,such as pavement collapse,are rather clear.Limited by historical and technical factors,the subgr...In comparison to the construction of modern highway engineering,several of China’s early pavement construction concerns,such as pavement collapse,are rather clear.Limited by historical and technical factors,the subgrade and pavement design for highways lacks scientificity,thus inducing potential safety problems in the operation.In order to comprehensively improve the subgrade and pavement design as well as ensure the quality and safety of highway engineering projects,this paper takes the reconstructed and expanded highway projects as research subjects and focuses on proposing optimization measures for the subgrade and pavement design of reconstructed and expanded highways,so as to provide adequate reference.展开更多
A neutrosophic multi-valued set(NMVS)is a crucial representation for true,false,and indeterminate multivalued information.Then,a consistent single-valued neutrosophic set(CSVNS)can effectively reflect the mean and con...A neutrosophic multi-valued set(NMVS)is a crucial representation for true,false,and indeterminate multivalued information.Then,a consistent single-valued neutrosophic set(CSVNS)can effectively reflect the mean and consistency degree of true,false,and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS.However,there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature.This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting.The cosine similarity measures showthe cosine of the angle between two vectors projected into amultidimensional space,rather than their distance.The cotangent similaritymeasures in this study can alleviate several shortcomings of cosine similarity measures in vector space to a certain extent.Then,a decisionmaking approach is presented in viewof the established cotangent similarity measures in the case of NMVSs.Finally,the developed decision-making approach is applied to selection problems of potential cars.The proposed approach has obtained two different results,which have the same sort sequence as the compared literature.The decision results prove its validity and effectiveness.Meantime,it also provides a new manner for neutrosophic multi-valued decision-making issues.展开更多
Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily appli...Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.展开更多
The analysis of existing method for calculation of total content of electrons (TEC) in ionosphere using GPS occultation method does show that due to different values of signal/noise ration in GPS signals ?and , the ne...The analysis of existing method for calculation of total content of electrons (TEC) in ionosphere using GPS occultation method does show that due to different values of signal/noise ration in GPS signals ?and , the new method of optimum measurements of relevant frequency components of TEC measured by phase and code methods should be developed. The optimum quantity of measurements of the above-mentioned frequency components is determined taking into account the limitation imposed on general number of necessary measurements.展开更多
Studying tiie urban landscape pattern plays a crucial role in scientific land use and management and in improving the urban ecological environment In this paper, AutoCAD, ArcGIS, Fragstats, and other software were u...Studying tiie urban landscape pattern plays a crucial role in scientific land use and management and in improving the urban ecological environment In this paper, AutoCAD, ArcGIS, Fragstats, and other software were used to analyse the data of the fourth phase of land use in the core atea of Yangling Demonstration Zone. The results showed that： ① in the core area, the percentage of construction land incteased from 18.22% to 61.72%, and the percentage of agricultufal land decreased from 58.36% to 11.14%. And the fafm land was fragmented, and traffic connectivily was strengthened. The afea of garden land was reduced from 251.89 hm2 to 50.38 hm^2, and the landscape metric of forest land showed an inverted V-shaped curve. ②The year 2009 in four phases witnessed the greatest landscape fragmentation, both Edge Density （ED） and Ingest Patch Index （LPI） increased, and human interference enhanced the overall landscape complexity. Measures were fotmulated in terms of deaf development goals, optimized allocation of land resoutces, effective protection of ecological ted lines, and definite ecological responsibility, so as to optimize the urban landscape pattern.展开更多
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
文摘The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
文摘In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.
基金Projects(51775445,52175435)supported by the National Natural Science Foundation of ChinaProject(CX2023051)supported by the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University,China。
文摘On-machine measurement(OMM)stands out as a pivotal technology in complex curved surface adaptive machining.However,the complex structure inherent in workpieces poses a significant challenge as the stylus orientation frequently shifts during the measurement process.Consequently,a substantial amount of time is allocated to calibrating pre-travel error and probe movement.Furthermore,the frequent movement of machine tools also increases the influence of machine errors.To enhance both accuracy and efficiency,an optimization strategy for the OMM process is proposed.Based on the kinematic chain of the machine tools,the relationship between the angle combination of rotary axes,the stylus orientation,and the calibration position of pre-travel error is disclosed.Additionally,an OMM efficiency optimization model for complex curved surfaces is developed.This model is solved to produce the optimal efficiency angle combinations for each to-be-measured point.Within each angle combination,the effects of positioning errors on measurement results are addressed by coordinate system offset and measurement result compensation method.Finally,the experiments on an impeller are used to demonstrate the practical utility of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant No.52179105)China Postdoctoral Science Foundation(Grant No.2024M762193)。
文摘In tunnel construction,tunnel boring machine(TBM)tunnelling typically relies on manual experience with sub-optimal control parameters,which can easily lead to inefficiency and high costs.This study proposed an intelligent decision-making method for TBM tunnelling control parameters based on multiobjective optimization(MOO).First,the effective TBM operation dataset is obtained through data preprocessing of the Songhua River(YS)tunnel project in China.Next,the proposed method begins with developing machine learning models for predicting TBM tunnelling performance parameters(i.e.total thrust and cutterhead torque),rock mass classification,and hazard risks(i.e.tunnel collapse and shield jamming).Then,considering three optimal objectives,(i.e.,penetration rate,rock-breaking energy consumption,and cutterhead hob wear),the MOO framework and corresponding mathematical expression are established.The Pareto optimal front is solved using DE-NSGA-II algorithm.Finally,the optimal control parameters(i.e.,advance rate and cutterhead rotation speed)are obtained by the satisfactory solution determination criterion,which can balance construction safety and efficiency with satisfaction.Furthermore,the proposed method is validated through 50 cases of TBM tunnelling,showing promising potential of application.
文摘Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.
基金supported by the National Natural Science Foundation of China under Grant T2521006,Grant 62403483,Grant 62533021 and Grant U24A20279.
文摘Reinforcement learning(RL)has been widely studied as an efficient class of machine learning methods for adaptive optimal control under uncertainties.In recent years,the applications of RL in optimised decision-making and motion control of intelligent vehicles have received increasing attention.Due to the complex and dynamic operating environments of intelligent vehicles,it is necessary to improve the learning efficiency and generalisation ability of RL-based decision and control algorithms under different conditions.This survey systematically examines the theoretical foundations,algorithmic advancements and practical challenges of applying RL to intelligent vehicle systems operating in complex and dynamic environments.The major algorithm frameworks of RL are first introduced,and the recent advances in RL-based decision-making and control of intelligent vehicles are overviewed.In addition to self-learning decision and control approaches using state measurements,the developments of DRL methods for end-to-end driving control of intelligent vehicles are summarised.The open problems and directions for further research works are also discussed.
基金Projects(51705446,51890881) supported by the National Natural Science Foundation of China
文摘This study was conducted to investigate the flow field characteristics of right-angled flow passage with various cavities in the typical hydraulic manifold block.A low-speed visualization test rig was developed and the flow field of the right-angled flow passage with different cavity structures was measured using 2D-PIV technique.Numerical model was established to simulate the three-dimensional flow field.Seven eddy viscosity turbulence models were investigated in predicting the flow field by comparing against the particle image relocimetry(PIV)measurement results.By defining the weight error function K,the S-A model was selected as the appropriate turbulence model.Then,a three-factor,three-level response surface numerical test was conducted to investigate the influence of flow passage connection type,cavity diameter and cavity length-diameter ratio on pressure loss.The results show that the Box-Benhnken Design(BBD)model can predict the total pressure loss accurately.The optimal factor level appeared in flow passage connection type II,14.64 mm diameter and 67.53%cavity length-diameter ratio.The total pressure loss decreased by 11.15%relative to the worst factor level,and total pressure loss can be reduced by 64.75%when using an arc transition right-angled flow passage,which indicates a new direction for the optimization design of flow passage in hydraulic manifold blocks.
基金Project(2007CB209402) supported by the National Basic Research Program of China Project(SKLGDUEK0906) supported by the Research Fund of State Key Laboratory for Geomechanics and Deep Underground Engineering of China
文摘An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.
基金co-supported by the National Key Research and Development Project of China(No.2018YFA0703304)the High-level Personnel Innovation Support Program of Dalian(No.2017RJ04)+2 种基金Youth Program of National Natural Science Foundation of China(No.51905077)Liaoning Revitalization Talents Program(No.XLYC1807086)China Postdoctoral Science Foundation Grand(No.2019M651110)。
文摘The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively.
基金the financial support by the National Key Research and Development Program of China(Grant No.2020YFC1808102)the Natural Science Foundation of China(No.51874328 and No.52074311)。
文摘Optimization of fracturing perforation is of great importance to the commingling gas production in coal measure strata.In this paper,a 3 D lattice algorithm hydraulic fracturing simulator was employed to study the effects of perforation position and length on hydraulic fracture propagation in coal measures of the Lin-Xing block,China.Based on field data,three lithologic combinations are simulated:1)a thick section of coal seam sandwiched by sandstones;2)a thin coal seam layer overlay by gas-bearing tight sandstone;3)two coal seams separated by a thin layer of sandstone.Our simulation shows that perforation position and length in multi-layer reservoirs play a major role in hydraulic fracture propagation.Achieving maximum stimulated volume requires consideration of lithologic sequence,coal seam thickness,stress states,and rock properties.To improve the combined gas production in coal measure strata,it is possible to simultaneously stimulate multiple coal seams or adjacent gas-bearing sandstones.In these cases,perforation location and length also significantly impact fracture propagation,and therefore should be carefully designed.Our simulation results using 3 D lattice algorithm are qualitatively consistent with laboratory physical simulation.3 D lattice models can be used to effectively simulate the fracture propagation through layers in coal measure strata.The numerical results provide guidance for perforation optimization in the hydraulic fracturing of coal measure strata.
基金Project(Z132012) supported by the Second Five Technology-based Fund in Science and Industry Bureau of ChinaProject(1004GK0032) supported by General Armament Department for the Common Issues of Military Electronic Components,China
文摘A lifetime prediction method for high-reliability tantalum （Ta） capacitors was proposed, based on multiple degradation measures and grey model （GM）. For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization （PSO） was used. Then, the new PSO-GM（1, 2, co） optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.
基金supported by the National Natural Science Foundation of China(No.62003280)Chongqing Talents:Exceptional Young Talents Project(No.cstc2022ycjhbgzxm0070)+1 种基金Natural Science Foundation of Chongqing,China(No.CSTB2022NSCQ-MSX0531)Chongqing Overseas Scholars Innovation Program(No.cx2022024).
文摘D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure.However,the mass assignments given by unknown information sources are disordered.How to measure the difference between the mass assignments has aroused people’s interest.In this paper,inspired by the information volume,a novel distance-based measure is proposed to measure the difference between mass assignments.The method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass assignments.At the same time,it is verified that the measure not only meets the properties of distance,but also proves the superiority of the proposed Information Volume Distance(IVD)through simulation experiments.Meanwhile,in the process of information fusion,the reliability of each source could be quantified through IVD.Therefore,based on IVD,a new multi-source information algorithm is proposed to solve the problem of multi-source information fusion.Moreover,algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness.
文摘A new method of phase measurement based on optimization is presented. Simulations were ran with synthesized signals, and comparison was made with some spectral domain methods. The results show that, with a suitable number of samples processed, this method is superior to other methods in terms of accuracy, while the amplitude and phase of distortion component have no effect on accuracy.
文摘In comparison to the construction of modern highway engineering,several of China’s early pavement construction concerns,such as pavement collapse,are rather clear.Limited by historical and technical factors,the subgrade and pavement design for highways lacks scientificity,thus inducing potential safety problems in the operation.In order to comprehensively improve the subgrade and pavement design as well as ensure the quality and safety of highway engineering projects,this paper takes the reconstructed and expanded highway projects as research subjects and focuses on proposing optimization measures for the subgrade and pavement design of reconstructed and expanded highways,so as to provide adequate reference.
文摘A neutrosophic multi-valued set(NMVS)is a crucial representation for true,false,and indeterminate multivalued information.Then,a consistent single-valued neutrosophic set(CSVNS)can effectively reflect the mean and consistency degree of true,false,and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS.However,there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature.This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting.The cosine similarity measures showthe cosine of the angle between two vectors projected into amultidimensional space,rather than their distance.The cotangent similaritymeasures in this study can alleviate several shortcomings of cosine similarity measures in vector space to a certain extent.Then,a decisionmaking approach is presented in viewof the established cotangent similarity measures in the case of NMVSs.Finally,the developed decision-making approach is applied to selection problems of potential cars.The proposed approach has obtained two different results,which have the same sort sequence as the compared literature.The decision results prove its validity and effectiveness.Meantime,it also provides a new manner for neutrosophic multi-valued decision-making issues.
文摘Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.
文摘The analysis of existing method for calculation of total content of electrons (TEC) in ionosphere using GPS occultation method does show that due to different values of signal/noise ration in GPS signals ?and , the new method of optimum measurements of relevant frequency components of TEC measured by phase and code methods should be developed. The optimum quantity of measurements of the above-mentioned frequency components is determined taking into account the limitation imposed on general number of necessary measurements.
基金Sponsored by Humanities and Social Sciences Project in Northwest A&F University(2015RWYB38)
文摘Studying tiie urban landscape pattern plays a crucial role in scientific land use and management and in improving the urban ecological environment In this paper, AutoCAD, ArcGIS, Fragstats, and other software were used to analyse the data of the fourth phase of land use in the core atea of Yangling Demonstration Zone. The results showed that： ① in the core area, the percentage of construction land incteased from 18.22% to 61.72%, and the percentage of agricultufal land decreased from 58.36% to 11.14%. And the fafm land was fragmented, and traffic connectivily was strengthened. The afea of garden land was reduced from 251.89 hm2 to 50.38 hm^2, and the landscape metric of forest land showed an inverted V-shaped curve. ②The year 2009 in four phases witnessed the greatest landscape fragmentation, both Edge Density （ED） and Ingest Patch Index （LPI） increased, and human interference enhanced the overall landscape complexity. Measures were fotmulated in terms of deaf development goals, optimized allocation of land resoutces, effective protection of ecological ted lines, and definite ecological responsibility, so as to optimize the urban landscape pattern.
