In this study, Imperialistic Competitive Algorithm（ICA） is utilized for locating the critical failure surface and computing the factor of safety（FOS） in a slope stability analysis based on the limit equilibrium ap...In this study, Imperialistic Competitive Algorithm（ICA） is utilized for locating the critical failure surface and computing the factor of safety（FOS） in a slope stability analysis based on the limit equilibrium approach. The factor of safety relating to each trial slip surface is calculated using a simplified algorithm of the Morgenstern-Price method, which satisfies both the force and the moment equilibriums. General slip surface is considered non-circular in this study that is constituted by linking random straight lines.To explore the performance of the proposed algorithm, four benchmark test problems are analyzed. The results demonstrate that the present techniques can provide reliable, accurate and efficient solutions for locating the critical failure surface and relating FOS. Moreover, in contrast with previous studies the present algorithm could reach the lower value of FOS and reached more exact solutions.展开更多
Autism spectrum disorder(ASD),classified as a developmental disability,is now more common in children than ever.A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection ...Autism spectrum disorder(ASD),classified as a developmental disability,is now more common in children than ever.A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in children.Parents can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five years.This research study aims to develop an automated tool for diagnosing autism in children.The computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition,feature selection,and classification phases.The most deterministic features are selected from the self-acquired dataset by novel feature selection methods before classification.The Imperialistic competitive algorithm(ICA)based on empires conquering colonies performs feature selection in this study.The performance of Logistic Regression(LR),Decision tree,K-Nearest Neighbor(KNN),and Random Forest(RF)classifiers are experimentally studied in this research work.The experimental results prove that the Logistic regression classifier exhibits the highest accuracy for the self-acquired dataset.The ASD detection is evaluated experimentally with the Least Absolute Shrinkage and Selection Operator(LASSO)feature selection method and different classifiers.The Exploratory Data Analysis(EDA)phase has uncovered crucial facts about the data,like the correlation of the features in the dataset with the class variable.展开更多
The optimal setting of directional overcurrent relays(DOCRs)ensures the fault detection and clearing in the minimum possible operation time.Directional protective relaying is carried out to coordinate relay settings i...The optimal setting of directional overcurrent relays(DOCRs)ensures the fault detection and clearing in the minimum possible operation time.Directional protective relaying is carried out to coordinate relay settings in a meshed network in the presence of distributed generation.The main goal of DOCR coordination is to find the optimal time dial setting(TDS)and pickup multiplier setting(PMS)to reach the minimum total operation time of all primary relays in the presence of coordination constraints.Due to the complexity of mixed integer non-linear programming(MINLP)problem,imperialistic competition algorithm(ICA)as a powerful evolutionary algorithm is used to solve the coordination problem of DOCRs.The proposed DOCR coordination formulation is implemented in three different test cases.The results are compared with the standard branch-and-bound algorithm and other meta-heuristic optimization algorithms,which demonstrates the effectiveness of the proposed algorithm.展开更多
Purpose–The purpose of this paper is to describe imperialist competitive algorithm(ICA),a novel socio-politically inspired optimization strategy for proposing a fuzzy variant of this algorithm.ICA is a meta-heuristic...Purpose–The purpose of this paper is to describe imperialist competitive algorithm(ICA),a novel socio-politically inspired optimization strategy for proposing a fuzzy variant of this algorithm.ICA is a meta-heuristic algorithm for dealing with different optimization tasks.The basis of the algorithm is inspired by imperialistic competition.It attempts to present the social policy of imperialisms(referred to empires)to control more countries(referred to colonies)and use their sources.If one empire loses its power,among the others making a competition to take possession of it.Design/methodology/approach–In fuzzy imperialist competitive algorithm(FICA),the colonies have a degree of belonging to their imperialists and the top imperialist,as in fuzzy logic,rather than belonging completely to just one empire therefore the colonies move toward the superior empire and their relevant empires.Simultaneously for balancing the exploration and exploitation abilities of the ICA.The algorithms are used for optimization have shortcoming to deal with accuracy rate and local optimum trap and they need complex tuning procedures.FICA is proposed a way for optimizing convex function with high accuracy and avoiding to trap in local optima rather than using original ICA algorithm by implementing fuzzy logic on it.Findings–Therefore several solution procedures,including ICA,FICA,genetic algorithm,particle swarm optimization,tabu search and simulated annealing optimization algorithm are considered.Finally numerical experiments are carried out to evaluate the effectiveness of models as well as solution procedures.Test results present the suitability of the proposed fuzzy ICA for convex functions with little fluctuations.Originality/value–The proposed evolutionary algorithm,FICA,can be used in diverse areas of optimization problems where convex functions properties are appeared including,industrial planning,resource allocation,scheduling,decision making,pattern recognition and machine learning(optimization techniques;fuzzy logic;convex functions).展开更多
Author:Hu Yan.This book provides a comprehensive overview of the background,causes,process,and impact of the British invasion of Xizang from 1903 to 1904,offering an in-depth analysis of the nature and detrimental act...Author:Hu Yan.This book provides a comprehensive overview of the background,causes,process,and impact of the British invasion of Xizang from 1903 to 1904,offering an in-depth analysis of the nature and detrimental actions of imperialist aggression.展开更多
This paper introduces a simple yet effective approach for developing fuzzy logic controllers(FLCs)to identify the maximum power point(MPP)and optimize the photovoltaic(PV)system to extract the maximum power in differe...This paper introduces a simple yet effective approach for developing fuzzy logic controllers(FLCs)to identify the maximum power point(MPP)and optimize the photovoltaic(PV)system to extract the maximum power in different environmental conditions.We propose a robust FLC with low computational complexity by reducing the number of membership functions and rules.To optimize the performance of the FLC,metaheuristic algorithms are employed to determine the parameters of the FLC.We evaluate the proposed FLC in various panel configurations under different environmental conditions.The results indicate that the proposed FLC can easily adapt to various panel configurations and perform better than other benchmarks in terms of enhanced stability,responsiveness,and power transfer under various scenarios.展开更多
This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed...This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed,placed in a sandbox,and then the sandbox is positioned on a BPM formoulding.The complexity of the scheduling problem increases due to the consideration of BPM capacity and sandbox volume.To minimize the makespan,a new cooperated imperialist competitive algorithm(CICA)is introduced.In CICA,the number of empires is not a parameter,and four empires aremaintained throughout the search process.Two types of assimilations are achieved:The strongest and weakest empires cooperate in their assimilation,while the remaining two empires,having a close normalization total cost,combine in their assimilation.A new form of imperialist competition is proposed to prevent insufficient competition,and the unique features of the problem are effectively utilized.Computational experiments are conducted across several instances,and a significant amount of experimental results show that the newstrategies of CICAare effective,indicating promising advantages for the considered BPMscheduling problems.展开更多
This study aims to develop several optimization techniques for predicting advance rate of tunnel boring machine(TBM)in different weathered zones of granite.For this purpose,extensive field and laboratory studies have ...This study aims to develop several optimization techniques for predicting advance rate of tunnel boring machine(TBM)in different weathered zones of granite.For this purpose,extensive field and laboratory studies have been conducted along the 12,649 m of the Pahang-Selangor raw water transfer tunnel in Malaysia.Rock properties consisting of uniaxial compressive strength(UCS),Brazilian tensile strength(BTS),rock mass rating(RMR),rock quality designation(RQD),quartz content(q)and weathered zone as well as machine specifications including thrust force and revolution per minute(RPM)were measured to establish comprehensive datasets for optimization.Accordingly,to estimate the advance rate of TBM,two new hybrid optimization techniques,i.e.an artificial neural network(ANN)combined with both imperialist competitive algorithm(ICA)and particle swarm optimization(PSO),were developed for mechanical tunneling in granitic rocks.Further,the new hybrid optimization techniques were compared and the best one was chosen among them to be used for practice.To evaluate the accuracy of the proposed models for both testing and training datasets,various statistical indices including coefficient of determination(R^2),root mean square error(RMSE)and variance account for(VAF)were utilized herein.The values of R^2,RMSE,and VAF ranged in 0.939-0.961,0.022-0.036,and 93.899-96.145,respectively,with the PSO-ANN hybrid technique demonstrating the best performance.It is concluded that both the optimization techniques,i.e.PSO-ANN and ICA-ANN,could be utilized for predicting the advance rate of TBMs;however,the PSO-ANN technique is superior.展开更多
Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization （RBDO...Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization （RBDO） offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliabil- ity strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reli- ability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its a-percentile per- formance, thereby avoiding convergence failure, calcula- tion error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.展开更多
Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department t...Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department to have sufficient time to formulate corresponding traffic flow control measures.In hence,it is meaningful to establish an accurate short-term traffic flow method and provide reference for peak traffic flow warning.This paper proposed a new hybrid model for traffic flow forecasting,which is composed of the variational mode decomposition(VMD)method,the group method of data handling(GMDH)neural network,bi-directional long and short term memory(BILSTM)network and ELMAN network,and is optimized by the imperialist competitive algorithm(ICA)method.To illustrate the performance of the proposed model,there are several comparative experiments between the proposed model and other models.The experiment results show that 1)BILSTM network,GMDH network and ELMAN network have better predictive performance than other single models;2)VMD can significantly improve the predictive performance of the ICA-GMDH-BILSTM-ELMAN model.The effect of VMD method is better than that of EEMD method and FEEMD method.To conclude,the proposed model which is made up of the VMD method,the ICA method,the BILSTM network,the GMDH network and the ELMAN network has excellent predictive ability for traffic flow series.展开更多
Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data ...Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.展开更多
This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular wa...This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves’ behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method’s efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.展开更多
A single machine-infinite-bus(SMIB) system including the interline power flow controllers(IPFCs) and the power system stabilizer(PSS) controller is addressed. The linearized system model is considered for investigatin...A single machine-infinite-bus(SMIB) system including the interline power flow controllers(IPFCs) and the power system stabilizer(PSS) controller is addressed. The linearized system model is considered for investigating the interactions among IPFC and PSS controllers. To improve the stability of whole system again different disturbances, a lead-lag controller is considered to produce supplementary signal. The proposed supplementary controller is implemented to improve the damping of the power system low frequency oscillations(LFOs). Imperialist optimization algorithm(ICA) and shuffled frog leaping algorithm(SFLA) are implemented to search for optimal supplementary controllers and PSS parameters. Moreover, singular value decomposition(SVD) method is utilized to select the most effective damping control signal of IPFC lead-lag controllers. To evaluate the system performance, different operating conditions are considered. Reponses of system in five modes including uncoordinated and coordinated modes of IPFC and PSS using ICA and SFLA are studied and compared. Considering the results, response of system without controller shows the highest overshoot and the longest settling time for rotor angel at the different operating conditions. In this mode of system, rotor speed has the highest overshoot. Rotor angel in the system with only PSS includes lower overshoot and oscillation than system without controller. When PSS is only implemented, rotor speed deviation has the longest settling time. Rotor speed deviation in the uncoordinated mode of IPFC and PSS shows lower overshoot than system with only PSS and without controller. It is noticeable that in this mode, rotor angel has higher overshoot than system with only PSS. The superiority of the suggested ICA-based coordinated controllers is obvious compared with SFLA-based coordinated controllers and other system modes. Responses of coordinated PSS and IPFC SFLA-based supplementary controllers include higher peak amplitude and longer settling time compared with coordinated IPFC and PSS ICA-based controllers. This comparison shows that overshoots, undershoots and the settling times are reduced considerably in coordinated mode of IPFC based controller and PSS using ICA. Analysis of the system performance shows that the proposed method has excellent response to different faults in power system.展开更多
The colonist culture of the imperialism nourished Jim＇s heroic dreams in which the protagonist sees himself as an apotheosis of morality and heroic deeds, but it also isolated him from the reality of the world. As a ...The colonist culture of the imperialism nourished Jim＇s heroic dreams in which the protagonist sees himself as an apotheosis of morality and heroic deeds, but it also isolated him from the reality of the world. As a result, he often finds himself caught in moral dilemmas and ends up making tragic choices. His tragedy indicated that the alluring and illusive myth of the imperialism was bound to fall apart.展开更多
The selection of machining parameters directly affects the production time,quality,cost,and other process performance measures for multi-pass milling.Optimization of machining parameters is of great significance.Howev...The selection of machining parameters directly affects the production time,quality,cost,and other process performance measures for multi-pass milling.Optimization of machining parameters is of great significance.However,it is a nonlinear constrained optimization problem,which is very difficult to obtain satisfactory solutions by traditional optimization methods.A new optimization technique combined chaotic operator and imperialist competitive algorithm(ICA)is proposed to solve this problem.The ICA simulates the competition between the empires.It is a population-based meta-heuristic algorithm for unconstrained optimization problems.Imperialist development operator based on chaotic sequence is introduced to improve the local search of ICA,while constraints handling mechanism is introduced and an imperialist-colony transformation policy is established.The improved ICA is called chaotic imperialist competitive algorithm(CICA).A case study of optimizing machining parameters for multi-pass face milling operations is presented to verify the effectiveness of the proposed method.The case is to optimize parameters such as speed,feed,and depth of cut in each pass have yielded a minimum total product ion cost.The depth of cut of optimal strategy obtained by CICA are 4 mm,3 mm,1 mm for rough cutting pass 1,rough cutting pass 1 and finish cutting pass,respectively.The cost for each pass are$0.5366 US,$0.4473 US and$0.3738 US.The optimal solution of CICA for various strategies with at=8 mm is$1.3576 US.The results obtained with the proposed schemes are better than those of previous work.This shows the superior performance of CICA in solving such problems.Finally,optimization of cutting strategy when the width of workpiece no smaller than the diameter of cutter is discussed.Conclusion can be drawn that larger tool diameter and row spacing should be chosen to increase cutting efficiency.展开更多
An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accur...An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation(BP) type neural network and imperialist competitive algorithm. The proposed method offers the advantage of local search ability of BP technique and global search ability of imperialist competitive algorithm. Two types of empirical data regarding the energy demand(gross domestic product(GDP), population, import, export and energy demand) in Turkey from 1979 to 2005 and electricity demand(population, GDP, total revenue from exporting industrial products and electricity consumption) in Thailand from 1986 to 2010 were investigated to demonstrate the applicability and merits of the present method. The performance of the proposed model is found to be better than that of conventional back-propagation neural network with low mean absolute error.展开更多
A hybrid intelligent method for evaluation of near optimal settings of friction welding process parameters of ductile iron was presented, The optimization of welding parameters was carried out in automatic cycle with ...A hybrid intelligent method for evaluation of near optimal settings of friction welding process parameters of ductile iron was presented, The optimization of welding parameters was carried out in automatic cycle with the use of support vector regression （SVR）, genetic algorithm （GA） and imperialist competitive algorithm （ICA）. The method suggested was used to determine welding process parameters by which the desired tensile strength was obtained in the friction welding of ductile iron. The highest tensile strength （TS） of 256.93 MPa was obtained using SVR plus GA method for the following friction welding parameters： heating force 40 kN, heating time 300 s and upsetting force 10.12 kN. The samples were welded by friction and subjected to the tensile strength test. The optimized values obtained by means of these hybrid techniques were compared with the experimental results. The application of hybrid intelligent methods allowed to increase the tensile strength joints from 211 to 258 MPa for the friction welder ZT-14 type.展开更多
In this paper, a new evolutionary algorithm, the well-known imperialist competition algorithm, is proposed for optimizing the optical thin-films. In this method, the process is modeled of the competition between count...In this paper, a new evolutionary algorithm, the well-known imperialist competition algorithm, is proposed for optimizing the optical thin-films. In this method, the process is modeled of the competition between countries as imperialists and their colonizing of others as colonies. This algorithm could be an appropriate alternative to some of the more popular algorithms for optimizing the optical thin-films for good performance. The polarizer and edge filter for example are designed by using the imperialist competition algorithm method and the results are compared with those from two optimization high-performance methods： the genetic algorithm and differential evolutionary algorithm. Based on these results,the performance of the imperialist competition algorithm method shows that this algorithm is not sensitive to the change of its parameters and it can be an important advantage for quickly achieving a global optimal point. On the other hand the results show a better ratio of P-polarization transmittance to S-polarization transmittance in the design of a 1540-nm polarizer, which is more appropriate than the results from the other two methods. In the second design, an edge filter with a lower number of layers and more uniform bandpass spectrum than the counterparts of those methods is obtained. These results indicate that the imperialist competition algorithm is a robust method for optical thin-film designs.展开更多
The original fault data of oil immersed transformer often contains a large number of unnecessary attributes,which greatly increases the elapsed time of the algorithm and reduces the classification accuracy,leading to ...The original fault data of oil immersed transformer often contains a large number of unnecessary attributes,which greatly increases the elapsed time of the algorithm and reduces the classification accuracy,leading to the rise of the diagnosis error rate.Therefore,in order to obtain high quality oil immersed transformer fault attribute data sets,an improved imperialist competitive algorithm was proposed to optimize the rough set to discretize the original fault data set and the attribute reduction.The feasibility of the proposed algorithm was verified by experiments and compared with other intelligent algorithms.Results show that the algorithm was stable at the 27th iteration with a reduction rate of 56.25%and a reduction accuracy of 98%.By using BP neural network to classify the reduction results,the accuracy was 86.25%,and the overall effect was better than those of the original data and other algorithms.Hence,the proposed method is effective for fault attribute reduction of oil immersed transformer.展开更多
With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possi...With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possible higher transmission capacity is very cost-effective.In this regard,to increase the capacity of the transmission lines,the flexible alternating current transmission system(FACTS)has been widely used in power grids in recent years by industrialized countries.One of the essential topics in electrical power systems is the reactive power compensation,and the FACTS plays a significant role in controlling the reactive power current in the power grid and the system voltage oscillations and stability.When a static synchronous compensator(STATCOM)is embedded in a power system to increase the bus voltage,a supplementary damping controller can be designed to enhance the system oscillation damping.Given the expansion of the grids in the power system,the complexity of their optimization and the extraordinary ability of the imperialist competitive algorithm(ICA)for solving such problems,in this paper,the ICA has been used to determine the optimal position and size of the FACTS devices.展开更多
文摘In this study, Imperialistic Competitive Algorithm（ICA） is utilized for locating the critical failure surface and computing the factor of safety（FOS） in a slope stability analysis based on the limit equilibrium approach. The factor of safety relating to each trial slip surface is calculated using a simplified algorithm of the Morgenstern-Price method, which satisfies both the force and the moment equilibriums. General slip surface is considered non-circular in this study that is constituted by linking random straight lines.To explore the performance of the proposed algorithm, four benchmark test problems are analyzed. The results demonstrate that the present techniques can provide reliable, accurate and efficient solutions for locating the critical failure surface and relating FOS. Moreover, in contrast with previous studies the present algorithm could reach the lower value of FOS and reached more exact solutions.
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number(IF2-PSAU-2022/01/22043)。
文摘Autism spectrum disorder(ASD),classified as a developmental disability,is now more common in children than ever.A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in children.Parents can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five years.This research study aims to develop an automated tool for diagnosing autism in children.The computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition,feature selection,and classification phases.The most deterministic features are selected from the self-acquired dataset by novel feature selection methods before classification.The Imperialistic competitive algorithm(ICA)based on empires conquering colonies performs feature selection in this study.The performance of Logistic Regression(LR),Decision tree,K-Nearest Neighbor(KNN),and Random Forest(RF)classifiers are experimentally studied in this research work.The experimental results prove that the Logistic regression classifier exhibits the highest accuracy for the self-acquired dataset.The ASD detection is evaluated experimentally with the Least Absolute Shrinkage and Selection Operator(LASSO)feature selection method and different classifiers.The Exploratory Data Analysis(EDA)phase has uncovered crucial facts about the data,like the correlation of the features in the dataset with the class variable.
文摘The optimal setting of directional overcurrent relays(DOCRs)ensures the fault detection and clearing in the minimum possible operation time.Directional protective relaying is carried out to coordinate relay settings in a meshed network in the presence of distributed generation.The main goal of DOCR coordination is to find the optimal time dial setting(TDS)and pickup multiplier setting(PMS)to reach the minimum total operation time of all primary relays in the presence of coordination constraints.Due to the complexity of mixed integer non-linear programming(MINLP)problem,imperialistic competition algorithm(ICA)as a powerful evolutionary algorithm is used to solve the coordination problem of DOCRs.The proposed DOCR coordination formulation is implemented in three different test cases.The results are compared with the standard branch-and-bound algorithm and other meta-heuristic optimization algorithms,which demonstrates the effectiveness of the proposed algorithm.
文摘Purpose–The purpose of this paper is to describe imperialist competitive algorithm(ICA),a novel socio-politically inspired optimization strategy for proposing a fuzzy variant of this algorithm.ICA is a meta-heuristic algorithm for dealing with different optimization tasks.The basis of the algorithm is inspired by imperialistic competition.It attempts to present the social policy of imperialisms(referred to empires)to control more countries(referred to colonies)and use their sources.If one empire loses its power,among the others making a competition to take possession of it.Design/methodology/approach–In fuzzy imperialist competitive algorithm(FICA),the colonies have a degree of belonging to their imperialists and the top imperialist,as in fuzzy logic,rather than belonging completely to just one empire therefore the colonies move toward the superior empire and their relevant empires.Simultaneously for balancing the exploration and exploitation abilities of the ICA.The algorithms are used for optimization have shortcoming to deal with accuracy rate and local optimum trap and they need complex tuning procedures.FICA is proposed a way for optimizing convex function with high accuracy and avoiding to trap in local optima rather than using original ICA algorithm by implementing fuzzy logic on it.Findings–Therefore several solution procedures,including ICA,FICA,genetic algorithm,particle swarm optimization,tabu search and simulated annealing optimization algorithm are considered.Finally numerical experiments are carried out to evaluate the effectiveness of models as well as solution procedures.Test results present the suitability of the proposed fuzzy ICA for convex functions with little fluctuations.Originality/value–The proposed evolutionary algorithm,FICA,can be used in diverse areas of optimization problems where convex functions properties are appeared including,industrial planning,resource allocation,scheduling,decision making,pattern recognition and machine learning(optimization techniques;fuzzy logic;convex functions).
文摘Author:Hu Yan.This book provides a comprehensive overview of the background,causes,process,and impact of the British invasion of Xizang from 1903 to 1904,offering an in-depth analysis of the nature and detrimental actions of imperialist aggression.
文摘This paper introduces a simple yet effective approach for developing fuzzy logic controllers(FLCs)to identify the maximum power point(MPP)and optimize the photovoltaic(PV)system to extract the maximum power in different environmental conditions.We propose a robust FLC with low computational complexity by reducing the number of membership functions and rules.To optimize the performance of the FLC,metaheuristic algorithms are employed to determine the parameters of the FLC.We evaluate the proposed FLC in various panel configurations under different environmental conditions.The results indicate that the proposed FLC can easily adapt to various panel configurations and perform better than other benchmarks in terms of enhanced stability,responsiveness,and power transfer under various scenarios.
基金the National Natural Science Foundation of China(Grant Number 61573264).
文摘This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed,placed in a sandbox,and then the sandbox is positioned on a BPM formoulding.The complexity of the scheduling problem increases due to the consideration of BPM capacity and sandbox volume.To minimize the makespan,a new cooperated imperialist competitive algorithm(CICA)is introduced.In CICA,the number of empires is not a parameter,and four empires aremaintained throughout the search process.Two types of assimilations are achieved:The strongest and weakest empires cooperate in their assimilation,while the remaining two empires,having a close normalization total cost,combine in their assimilation.A new form of imperialist competition is proposed to prevent insufficient competition,and the unique features of the problem are effectively utilized.Computational experiments are conducted across several instances,and a significant amount of experimental results show that the newstrategies of CICAare effective,indicating promising advantages for the considered BPMscheduling problems.
文摘This study aims to develop several optimization techniques for predicting advance rate of tunnel boring machine(TBM)in different weathered zones of granite.For this purpose,extensive field and laboratory studies have been conducted along the 12,649 m of the Pahang-Selangor raw water transfer tunnel in Malaysia.Rock properties consisting of uniaxial compressive strength(UCS),Brazilian tensile strength(BTS),rock mass rating(RMR),rock quality designation(RQD),quartz content(q)and weathered zone as well as machine specifications including thrust force and revolution per minute(RPM)were measured to establish comprehensive datasets for optimization.Accordingly,to estimate the advance rate of TBM,two new hybrid optimization techniques,i.e.an artificial neural network(ANN)combined with both imperialist competitive algorithm(ICA)and particle swarm optimization(PSO),were developed for mechanical tunneling in granitic rocks.Further,the new hybrid optimization techniques were compared and the best one was chosen among them to be used for practice.To evaluate the accuracy of the proposed models for both testing and training datasets,various statistical indices including coefficient of determination(R^2),root mean square error(RMSE)and variance account for(VAF)were utilized herein.The values of R^2,RMSE,and VAF ranged in 0.939-0.961,0.022-0.036,and 93.899-96.145,respectively,with the PSO-ANN hybrid technique demonstrating the best performance.It is concluded that both the optimization techniques,i.e.PSO-ANN and ICA-ANN,could be utilized for predicting the advance rate of TBMs;however,the PSO-ANN technique is superior.
基金Supported by National Natural Science Foundation of China(Grant No.51275329)
文摘Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization （RBDO） offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliabil- ity strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reli- ability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its a-percentile per- formance, thereby avoiding convergence failure, calcula- tion error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.
基金Project(61873283)supported by the National Natural Science Foundation of ChinaProject(KQ1707017)supported by the Changsha Science&Technology Project,ChinaProject(2019CX005)supported by the Innovation Driven Project of the Central South University,China。
文摘Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department to have sufficient time to formulate corresponding traffic flow control measures.In hence,it is meaningful to establish an accurate short-term traffic flow method and provide reference for peak traffic flow warning.This paper proposed a new hybrid model for traffic flow forecasting,which is composed of the variational mode decomposition(VMD)method,the group method of data handling(GMDH)neural network,bi-directional long and short term memory(BILSTM)network and ELMAN network,and is optimized by the imperialist competitive algorithm(ICA)method.To illustrate the performance of the proposed model,there are several comparative experiments between the proposed model and other models.The experiment results show that 1)BILSTM network,GMDH network and ELMAN network have better predictive performance than other single models;2)VMD can significantly improve the predictive performance of the ICA-GMDH-BILSTM-ELMAN model.The effect of VMD method is better than that of EEMD method and FEEMD method.To conclude,the proposed model which is made up of the VMD method,the ICA method,the BILSTM network,the GMDH network and the ELMAN network has excellent predictive ability for traffic flow series.
文摘Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.
文摘This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves’ behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method’s efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.
文摘A single machine-infinite-bus(SMIB) system including the interline power flow controllers(IPFCs) and the power system stabilizer(PSS) controller is addressed. The linearized system model is considered for investigating the interactions among IPFC and PSS controllers. To improve the stability of whole system again different disturbances, a lead-lag controller is considered to produce supplementary signal. The proposed supplementary controller is implemented to improve the damping of the power system low frequency oscillations(LFOs). Imperialist optimization algorithm(ICA) and shuffled frog leaping algorithm(SFLA) are implemented to search for optimal supplementary controllers and PSS parameters. Moreover, singular value decomposition(SVD) method is utilized to select the most effective damping control signal of IPFC lead-lag controllers. To evaluate the system performance, different operating conditions are considered. Reponses of system in five modes including uncoordinated and coordinated modes of IPFC and PSS using ICA and SFLA are studied and compared. Considering the results, response of system without controller shows the highest overshoot and the longest settling time for rotor angel at the different operating conditions. In this mode of system, rotor speed has the highest overshoot. Rotor angel in the system with only PSS includes lower overshoot and oscillation than system without controller. When PSS is only implemented, rotor speed deviation has the longest settling time. Rotor speed deviation in the uncoordinated mode of IPFC and PSS shows lower overshoot than system with only PSS and without controller. It is noticeable that in this mode, rotor angel has higher overshoot than system with only PSS. The superiority of the suggested ICA-based coordinated controllers is obvious compared with SFLA-based coordinated controllers and other system modes. Responses of coordinated PSS and IPFC SFLA-based supplementary controllers include higher peak amplitude and longer settling time compared with coordinated IPFC and PSS ICA-based controllers. This comparison shows that overshoots, undershoots and the settling times are reduced considerably in coordinated mode of IPFC based controller and PSS using ICA. Analysis of the system performance shows that the proposed method has excellent response to different faults in power system.
文摘The colonist culture of the imperialism nourished Jim＇s heroic dreams in which the protagonist sees himself as an apotheosis of morality and heroic deeds, but it also isolated him from the reality of the world. As a result, he often finds himself caught in moral dilemmas and ends up making tragic choices. His tragedy indicated that the alluring and illusive myth of the imperialism was bound to fall apart.
基金supported by the National Natural Science Foundation of China under grant no.51705182.
文摘The selection of machining parameters directly affects the production time,quality,cost,and other process performance measures for multi-pass milling.Optimization of machining parameters is of great significance.However,it is a nonlinear constrained optimization problem,which is very difficult to obtain satisfactory solutions by traditional optimization methods.A new optimization technique combined chaotic operator and imperialist competitive algorithm(ICA)is proposed to solve this problem.The ICA simulates the competition between the empires.It is a population-based meta-heuristic algorithm for unconstrained optimization problems.Imperialist development operator based on chaotic sequence is introduced to improve the local search of ICA,while constraints handling mechanism is introduced and an imperialist-colony transformation policy is established.The improved ICA is called chaotic imperialist competitive algorithm(CICA).A case study of optimizing machining parameters for multi-pass face milling operations is presented to verify the effectiveness of the proposed method.The case is to optimize parameters such as speed,feed,and depth of cut in each pass have yielded a minimum total product ion cost.The depth of cut of optimal strategy obtained by CICA are 4 mm,3 mm,1 mm for rough cutting pass 1,rough cutting pass 1 and finish cutting pass,respectively.The cost for each pass are$0.5366 US,$0.4473 US and$0.3738 US.The optimal solution of CICA for various strategies with at=8 mm is$1.3576 US.The results obtained with the proposed schemes are better than those of previous work.This shows the superior performance of CICA in solving such problems.Finally,optimization of cutting strategy when the width of workpiece no smaller than the diameter of cutter is discussed.Conclusion can be drawn that larger tool diameter and row spacing should be chosen to increase cutting efficiency.
文摘An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation(BP) type neural network and imperialist competitive algorithm. The proposed method offers the advantage of local search ability of BP technique and global search ability of imperialist competitive algorithm. Two types of empirical data regarding the energy demand(gross domestic product(GDP), population, import, export and energy demand) in Turkey from 1979 to 2005 and electricity demand(population, GDP, total revenue from exporting industrial products and electricity consumption) in Thailand from 1986 to 2010 were investigated to demonstrate the applicability and merits of the present method. The performance of the proposed model is found to be better than that of conventional back-propagation neural network with low mean absolute error.
文摘A hybrid intelligent method for evaluation of near optimal settings of friction welding process parameters of ductile iron was presented, The optimization of welding parameters was carried out in automatic cycle with the use of support vector regression （SVR）, genetic algorithm （GA） and imperialist competitive algorithm （ICA）. The method suggested was used to determine welding process parameters by which the desired tensile strength was obtained in the friction welding of ductile iron. The highest tensile strength （TS） of 256.93 MPa was obtained using SVR plus GA method for the following friction welding parameters： heating force 40 kN, heating time 300 s and upsetting force 10.12 kN. The samples were welded by friction and subjected to the tensile strength test. The optimized values obtained by means of these hybrid techniques were compared with the experimental results. The application of hybrid intelligent methods allowed to increase the tensile strength joints from 211 to 258 MPa for the friction welder ZT-14 type.
文摘In this paper, a new evolutionary algorithm, the well-known imperialist competition algorithm, is proposed for optimizing the optical thin-films. In this method, the process is modeled of the competition between countries as imperialists and their colonizing of others as colonies. This algorithm could be an appropriate alternative to some of the more popular algorithms for optimizing the optical thin-films for good performance. The polarizer and edge filter for example are designed by using the imperialist competition algorithm method and the results are compared with those from two optimization high-performance methods： the genetic algorithm and differential evolutionary algorithm. Based on these results,the performance of the imperialist competition algorithm method shows that this algorithm is not sensitive to the change of its parameters and it can be an important advantage for quickly achieving a global optimal point. On the other hand the results show a better ratio of P-polarization transmittance to S-polarization transmittance in the design of a 1540-nm polarizer, which is more appropriate than the results from the other two methods. In the second design, an edge filter with a lower number of layers and more uniform bandpass spectrum than the counterparts of those methods is obtained. These results indicate that the imperialist competition algorithm is a robust method for optical thin-film designs.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51504085)the Natural Science Foundation for Returness of Heilongjiang Province of China(Grant No.LC2017026).
文摘The original fault data of oil immersed transformer often contains a large number of unnecessary attributes,which greatly increases the elapsed time of the algorithm and reduces the classification accuracy,leading to the rise of the diagnosis error rate.Therefore,in order to obtain high quality oil immersed transformer fault attribute data sets,an improved imperialist competitive algorithm was proposed to optimize the rough set to discretize the original fault data set and the attribute reduction.The feasibility of the proposed algorithm was verified by experiments and compared with other intelligent algorithms.Results show that the algorithm was stable at the 27th iteration with a reduction rate of 56.25%and a reduction accuracy of 98%.By using BP neural network to classify the reduction results,the accuracy was 86.25%,and the overall effect was better than those of the original data and other algorithms.Hence,the proposed method is effective for fault attribute reduction of oil immersed transformer.
基金This work was supported in part by an International Research Partnership“Electrical Engineering-Thai French Research Center(EE-TFRC)”under the project framework of the Lorraine Universited’Excellence(LUE)in cooperation between Universitede Lorraine and King Mongkut’s University of Technology North Bangkok and in part by the National Research Council of Thailand(NRCT)under Senior Research Scholar Program under Grant No.N42A640328.
文摘With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possible higher transmission capacity is very cost-effective.In this regard,to increase the capacity of the transmission lines,the flexible alternating current transmission system(FACTS)has been widely used in power grids in recent years by industrialized countries.One of the essential topics in electrical power systems is the reactive power compensation,and the FACTS plays a significant role in controlling the reactive power current in the power grid and the system voltage oscillations and stability.When a static synchronous compensator(STATCOM)is embedded in a power system to increase the bus voltage,a supplementary damping controller can be designed to enhance the system oscillation damping.Given the expansion of the grids in the power system,the complexity of their optimization and the extraordinary ability of the imperialist competitive algorithm(ICA)for solving such problems,in this paper,the ICA has been used to determine the optimal position and size of the FACTS devices.
