This paper studies polygon simplification algorithms for 3D models,focuses on the optimization algorithm of quadratic error metric(QEM),explores the impacts of different methods on the simplification of different mode...This paper studies polygon simplification algorithms for 3D models,focuses on the optimization algorithm of quadratic error metric(QEM),explores the impacts of different methods on the simplification of different models,and develops a web-based visualization application.Metrics such as the Hausdorff distance are used to evaluate the balance between the degree of simplification and the retention of model details.展开更多
As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results a...As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements.Unfortunately,most existing indexes and ranking algo-rithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations,making it impossible to deliver exceptionally accurate results.As a result,this study investigates and analyses how search engines work,as well as the elements that contribute to higher ranks.This paper addresses the issue of bias by proposing a new ranking algorithm based on the PageRank(PR)algorithm,which is one of the most widely used page ranking algorithms We pro-pose weighted PageRank(WPR)algorithms to test the relationship between these various measures.The Weighted Page Rank(WPR)model was used in three dis-tinct trials to compare the rankings of documents and pages based on one or more user preferences criteria.Thefindings of utilizing the Weighted Page Rank model showed that using multiple criteria to rankfinal pages is better than using only one,and that some criteria had a greater impact on ranking results than others.展开更多
In order to rank searching results according to the user preferences,a new personalized web pages ranking algorithm called PWPR（personalized web page ranking）with the idea of adjusting the ranking scores of web page...In order to rank searching results according to the user preferences,a new personalized web pages ranking algorithm called PWPR（personalized web page ranking）with the idea of adjusting the ranking scores of web pages in accordance with user preferences is proposed.PWPR assigns the initial weights based on user interests and creates the virtual links and hubs according to user interests.By measuring user click streams,PWPR incrementally reflects users’ favors for the personalized ranking.To improve the accuracy of ranking, PWPR also takes collaborative filtering into consideration when the query with similar is submitted by users who have similar user interests. Detailed simulation results and comparison with other algorithms prove that the proposed PWPR can adaptively provide personalized ranking and truly relevant information to user preferences.展开更多
For the problem of dynamic optimization in Web services composition, this paper presents a novel approach for selecting optimum Web services, which is based on the longest path method of weighted multistage graph. We ...For the problem of dynamic optimization in Web services composition, this paper presents a novel approach for selecting optimum Web services, which is based on the longest path method of weighted multistage graph. We propose and implement an Immune Algorithm for global optimization to construct composed Web services. Results of the experimentation illustrates that the algorithm in this paper has a powerful capability and can greatly improve the efficiency and veracity in service selection.展开更多
Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services sele...Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.展开更多
Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm （TDSA）. The algorithm adopts the throughput of cluster back-ends to evaluate their load...Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm （TDSA）. The algorithm adopts the throughput of cluster back-ends to evaluate their load and employs the neural network model to predict the future load so that the scheduling system features a self-learning capability and good adaptability to the change of load. Moreover, it separates static requests from dynamic requests to make full use of the CPU resources and takes the locality of requests into account to improve the cache hit ratio. Experimental re suits from the testing tool of WebBench^TM show better per formance for Web cluster server with TDSA than that with traditional scheduling algorithms.展开更多
A new algorithm for solving the three-dimensional elastic contact problem with friction is presented. The algorithm is a non-interior smoothing algorithm based on an NCP-function. The parametric variational principle ...A new algorithm for solving the three-dimensional elastic contact problem with friction is presented. The algorithm is a non-interior smoothing algorithm based on an NCP-function. The parametric variational principle and parametric quadratic programming method were applied to the analysis of three-dimensional frictional contact problem. The solution of the contact problem was finally reduced to a linear complementarity problem, which was reformulated as a system of nonsmooth equations via an NCP-function. A smoothing approximation to the nonsmooth equations was given by the aggregate function. A Newton method was used to solve the resulting smoothing nonlinear equations. The algorithm presented is easy to understand and implement. The reliability and efficiency of this algorithm are demonstrated both by the numerical experiments of LCP in mathematical way and the examples of contact problems in mechanics.展开更多
Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a...Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.展开更多
The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based...The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.展开更多
In very short time today web has become an enormously important tool for communicating ideas, conducting business and entertainment. At the time of navigation, web users leave various records of their action. This vas...In very short time today web has become an enormously important tool for communicating ideas, conducting business and entertainment. At the time of navigation, web users leave various records of their action. This vast amount of data can be a useful source of knowledge for predicting user behavior. A refined method is required to carry out this task. Web usages mining (WUM) is the tool designed to do this task. WUM system is used to extract the knowledge based on user behavior during the web navigation. The extracted knowledge can be used for predicting the users’ future request when user is browsing the web. In this paper we advanced the online recommender system by using a Longest Common Subsequence (LCS) classification algorithm to classify users’ navigation pattern. Classification using the proposed method can improve the accuracy of recommendation and also proposed an algorithm that uses LCS method to know the user behavior for improvement of design of a website.展开更多
Web quality of service (QoS) awareness requires not only the selection of specific services to complete specific tasks, but also the comprehensive quality of service of the whole web service composition. How to select...Web quality of service (QoS) awareness requires not only the selection of specific services to complete specific tasks, but also the comprehensive quality of service of the whole web service composition. How to select the web service composition with the highest comprehensive QoS is a NP hard problem. In this paper, an improved multi population genetic algorithm is proposed. Cosine adaptive operator is added to the algorithm to avoid premature algorithm caused by improper genetic operator and the disadvantage of destroying excellent individuals in later period. Experimental results show that compared with the common genetic algorithm and multi population genetic algorithm, this algorithm has the advantages of shorter time consumption and higher accuracy, and effectively avoids the loss of effective genes in the population.展开更多
The paper mainly discusses the application of dynamic relevance feedback technique in Web intelligent retrieval and stresses the dynamic similarity in the course of feedback.It discusses the application of dynamic rel...The paper mainly discusses the application of dynamic relevance feedback technique in Web intelligent retrieval and stresses the dynamic similarity in the course of feedback.It discusses the application of dynamic relevance feedback technique from the Web page text and image aspects,and proposes to use the user interest model and the neural network to raise the precision and feasibility of the search result in relevant feedback.展开更多
With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evoluti...With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming （CSEP） algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering.展开更多
Web services are provided as reusable software components in the services-oriented architecture.More complicated composite services can be combined from these components to satisfy the user requirements represented as...Web services are provided as reusable software components in the services-oriented architecture.More complicated composite services can be combined from these components to satisfy the user requirements represented as a workflow with specified Quality of Service(QoS)limitations.The workflow consists of tasks where many services can be considered for each task.Searching for optimal services combination and optimizing the overall QoS limitations is a Non-deterministic Polynomial(NP)-hard problem.This work focuses on the Web Service Composition(WSC)problem and proposes a new service composition algorithm based on the micro-bats behavior while hunting the prey.The proposed algorithm determines the optimal combination of the web services to satisfy the complex user needs.It also addresses the Bat Algorithm(BA)shortcomings,such as the tradeoff among exploration and exploitation searching mechanisms,local optima,and convergence rate.The proposed enhancement includes a developed cooperative and adaptive population initialization mechanism.An elitist mechanism is utilized to address the BA convergence rate.The tradeoff between exploration and exploitation is handled through a neighborhood search mechanism.Several benchmark datasets are selected to evaluate the proposed bat algorithm’s performance.The simulation results are estimated using the average fitness value,the standard deviation of the fitness value,and an average of the execution time and compared with four bat-inspired algorithms.It is observed from the simulation results that introduced enhancement obtains significant results.展开更多
<div style="text-align:justify;"> <span style="font-family:Verdana;">There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of...<div style="text-align:justify;"> <span style="font-family:Verdana;">There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of a Web server being inundated with requests is ever-present. One approach to reducing the performance degradation that potentially comes from Web server overloading is to employ Web caching where data content is replicated in multiple locations. In this paper, we investigate the use of evolutionary algorithms to dynamically alter partition size in Web caches. We use established modeling techniques to compare the performance of our evolutionary algorithm to that found in statically-partitioned systems. Our results indicate that utilizing an evolutionary algorithm to dynamically alter partition sizes can lead to performance improvements especially in environments where the relative size of large to small pages is high.</span> </div>展开更多
In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these needs.The WSC’s main objective is to search for the optimal combination of web services ...In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these needs.The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services(QoS)constraints.The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints.In this paper,we introduce an extension of our previous works on the Artificial Bee Colony(ABC)and Bat Algorithm(BA).A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search.The bat agent is used to improve the solution of exhausted bees after a threshold(limits),and also an Elitist Strategy(ES)is added to BA to increase the convergence rate.The performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria(average fitness values,best fitness values,and execution time)that were measured for 30 different runs.These datasets are created from real-world datasets and artificially to form different scale sizes of WSC datasets.The results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to competitors.TheWilcoxon signed-rank significant test is usedwhere the proposed algorithm results significantly differ fromother algorithms on 100%of datasets.展开更多
Effect web will be an important combat means to achieve accurate,efficient,agile and reliable destruction of enemy targets.The use of Unmanned Aerial Vehicles(UAV)cluster in warfare has become a key element in the bat...Effect web will be an important combat means to achieve accurate,efficient,agile and reliable destruction of enemy targets.The use of Unmanned Aerial Vehicles(UAV)cluster in warfare has become a key element in the battle for military superiority between nations.The construction of UAV cluster effect web is a kind of combinatorial optimization in essence.By selecting the optimal combination in the limited equipment concentration,the whole network can be optimized.Firstly,in order to improve the combinatorial optimization efficiency of UAV cluster effect web,NSGA-Ⅱbased on deep Q-network(DQN-based NSGA-Ⅱ)is proposed.This algorithm is used to solve the Multi-Objective Combinatorial Optimization(MOCO)problem in the construction of effect web.Secondly,a dynamic generation method is devised to solve the problem caused by the possible destruction of enemy and our node under the fierce confrontation between the two sides.Finally,the simulation results show that the DQN-based NSGA-Ⅱis better than the genetic algorithm with single operator.The comparison experiment shows that the weight of evaluation indexes will have a corresponding influence on the optimization results.展开更多
文摘This paper studies polygon simplification algorithms for 3D models,focuses on the optimization algorithm of quadratic error metric(QEM),explores the impacts of different methods on the simplification of different models,and develops a web-based visualization application.Metrics such as the Hausdorff distance are used to evaluate the balance between the degree of simplification and the retention of model details.
文摘As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements.Unfortunately,most existing indexes and ranking algo-rithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations,making it impossible to deliver exceptionally accurate results.As a result,this study investigates and analyses how search engines work,as well as the elements that contribute to higher ranks.This paper addresses the issue of bias by proposing a new ranking algorithm based on the PageRank(PR)algorithm,which is one of the most widely used page ranking algorithms We pro-pose weighted PageRank(WPR)algorithms to test the relationship between these various measures.The Weighted Page Rank(WPR)model was used in three dis-tinct trials to compare the rankings of documents and pages based on one or more user preferences criteria.Thefindings of utilizing the Weighted Page Rank model showed that using multiple criteria to rankfinal pages is better than using only one,and that some criteria had a greater impact on ranking results than others.
基金The Natural Science Foundation of South-Central University for Nationalities(No.YZZ07006)
文摘In order to rank searching results according to the user preferences,a new personalized web pages ranking algorithm called PWPR（personalized web page ranking）with the idea of adjusting the ranking scores of web pages in accordance with user preferences is proposed.PWPR assigns the initial weights based on user interests and creates the virtual links and hubs according to user interests.By measuring user click streams,PWPR incrementally reflects users’ favors for the personalized ranking.To improve the accuracy of ranking, PWPR also takes collaborative filtering into consideration when the query with similar is submitted by users who have similar user interests. Detailed simulation results and comparison with other algorithms prove that the proposed PWPR can adaptively provide personalized ranking and truly relevant information to user preferences.
基金Supported by the National Key Technologies Re-search and Development Programinthe 10th Five-Year Plan of China(2004BA721A05)
文摘For the problem of dynamic optimization in Web services composition, this paper presents a novel approach for selecting optimum Web services, which is based on the longest path method of weighted multistage graph. We propose and implement an Immune Algorithm for global optimization to construct composed Web services. Results of the experimentation illustrates that the algorithm in this paper has a powerful capability and can greatly improve the efficiency and veracity in service selection.
基金Project(70631004)supported by the Key Project of the National Natural Science Foundation of ChinaProject(20080440988)supported by the Postdoctoral Science Foundation of China+1 种基金Project(09JJ4030)supported by the Natural Science Foundation of Hunan Province,ChinaProject supported by the Postdoctoral Science Foundation of Central South University,China
文摘Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.
基金Supported by the National Natural Science Funda-tion of China (60175015)
文摘Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm （TDSA）. The algorithm adopts the throughput of cluster back-ends to evaluate their load and employs the neural network model to predict the future load so that the scheduling system features a self-learning capability and good adaptability to the change of load. Moreover, it separates static requests from dynamic requests to make full use of the CPU resources and takes the locality of requests into account to improve the cache hit ratio. Experimental re suits from the testing tool of WebBench^TM show better per formance for Web cluster server with TDSA than that with traditional scheduling algorithms.
文摘A new algorithm for solving the three-dimensional elastic contact problem with friction is presented. The algorithm is a non-interior smoothing algorithm based on an NCP-function. The parametric variational principle and parametric quadratic programming method were applied to the analysis of three-dimensional frictional contact problem. The solution of the contact problem was finally reduced to a linear complementarity problem, which was reformulated as a system of nonsmooth equations via an NCP-function. A smoothing approximation to the nonsmooth equations was given by the aggregate function. A Newton method was used to solve the resulting smoothing nonlinear equations. The algorithm presented is easy to understand and implement. The reliability and efficiency of this algorithm are demonstrated both by the numerical experiments of LCP in mathematical way and the examples of contact problems in mechanics.
基金Supported by the National Natural Science Foundation of China(60472099)Ningbo Natural Science Foundation(2006A610017)
文摘Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.
文摘The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.
文摘In very short time today web has become an enormously important tool for communicating ideas, conducting business and entertainment. At the time of navigation, web users leave various records of their action. This vast amount of data can be a useful source of knowledge for predicting user behavior. A refined method is required to carry out this task. Web usages mining (WUM) is the tool designed to do this task. WUM system is used to extract the knowledge based on user behavior during the web navigation. The extracted knowledge can be used for predicting the users’ future request when user is browsing the web. In this paper we advanced the online recommender system by using a Longest Common Subsequence (LCS) classification algorithm to classify users’ navigation pattern. Classification using the proposed method can improve the accuracy of recommendation and also proposed an algorithm that uses LCS method to know the user behavior for improvement of design of a website.
文摘Web quality of service (QoS) awareness requires not only the selection of specific services to complete specific tasks, but also the comprehensive quality of service of the whole web service composition. How to select the web service composition with the highest comprehensive QoS is a NP hard problem. In this paper, an improved multi population genetic algorithm is proposed. Cosine adaptive operator is added to the algorithm to avoid premature algorithm caused by improper genetic operator and the disadvantage of destroying excellent individuals in later period. Experimental results show that compared with the common genetic algorithm and multi population genetic algorithm, this algorithm has the advantages of shorter time consumption and higher accuracy, and effectively avoids the loss of effective genes in the population.
文摘The paper mainly discusses the application of dynamic relevance feedback technique in Web intelligent retrieval and stresses the dynamic similarity in the course of feedback.It discusses the application of dynamic relevance feedback technique from the Web page text and image aspects,and proposes to use the user interest model and the neural network to raise the precision and feasibility of the search result in relevant feedback.
文摘With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming （CSEP） algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering.
基金The author extend their appreciation to Deputyship for research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number(IF-PSAU-2022/01/19619).
文摘Web services are provided as reusable software components in the services-oriented architecture.More complicated composite services can be combined from these components to satisfy the user requirements represented as a workflow with specified Quality of Service(QoS)limitations.The workflow consists of tasks where many services can be considered for each task.Searching for optimal services combination and optimizing the overall QoS limitations is a Non-deterministic Polynomial(NP)-hard problem.This work focuses on the Web Service Composition(WSC)problem and proposes a new service composition algorithm based on the micro-bats behavior while hunting the prey.The proposed algorithm determines the optimal combination of the web services to satisfy the complex user needs.It also addresses the Bat Algorithm(BA)shortcomings,such as the tradeoff among exploration and exploitation searching mechanisms,local optima,and convergence rate.The proposed enhancement includes a developed cooperative and adaptive population initialization mechanism.An elitist mechanism is utilized to address the BA convergence rate.The tradeoff between exploration and exploitation is handled through a neighborhood search mechanism.Several benchmark datasets are selected to evaluate the proposed bat algorithm’s performance.The simulation results are estimated using the average fitness value,the standard deviation of the fitness value,and an average of the execution time and compared with four bat-inspired algorithms.It is observed from the simulation results that introduced enhancement obtains significant results.
文摘<div style="text-align:justify;"> <span style="font-family:Verdana;">There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of a Web server being inundated with requests is ever-present. One approach to reducing the performance degradation that potentially comes from Web server overloading is to employ Web caching where data content is replicated in multiple locations. In this paper, we investigate the use of evolutionary algorithms to dynamically alter partition size in Web caches. We use established modeling techniques to compare the performance of our evolutionary algorithm to that found in statically-partitioned systems. Our results indicate that utilizing an evolutionary algorithm to dynamically alter partition sizes can lead to performance improvements especially in environments where the relative size of large to small pages is high.</span> </div>
基金The authors extend their appreciation to the Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number 2022/01/22636.
文摘In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these needs.The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services(QoS)constraints.The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints.In this paper,we introduce an extension of our previous works on the Artificial Bee Colony(ABC)and Bat Algorithm(BA).A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search.The bat agent is used to improve the solution of exhausted bees after a threshold(limits),and also an Elitist Strategy(ES)is added to BA to increase the convergence rate.The performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria(average fitness values,best fitness values,and execution time)that were measured for 30 different runs.These datasets are created from real-world datasets and artificially to form different scale sizes of WSC datasets.The results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to competitors.TheWilcoxon signed-rank significant test is usedwhere the proposed algorithm results significantly differ fromother algorithms on 100%of datasets.
基金co-supported by the Fundamental Research Funds for the Central Universities,China。
文摘Effect web will be an important combat means to achieve accurate,efficient,agile and reliable destruction of enemy targets.The use of Unmanned Aerial Vehicles(UAV)cluster in warfare has become a key element in the battle for military superiority between nations.The construction of UAV cluster effect web is a kind of combinatorial optimization in essence.By selecting the optimal combination in the limited equipment concentration,the whole network can be optimized.Firstly,in order to improve the combinatorial optimization efficiency of UAV cluster effect web,NSGA-Ⅱbased on deep Q-network(DQN-based NSGA-Ⅱ)is proposed.This algorithm is used to solve the Multi-Objective Combinatorial Optimization(MOCO)problem in the construction of effect web.Secondly,a dynamic generation method is devised to solve the problem caused by the possible destruction of enemy and our node under the fierce confrontation between the two sides.Finally,the simulation results show that the DQN-based NSGA-Ⅱis better than the genetic algorithm with single operator.The comparison experiment shows that the weight of evaluation indexes will have a corresponding influence on the optimization results.
