The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of s...The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.展开更多
This paper introduces an Improved Bidirectional Jump Point Search(I-BJPS)algorithm to address the challenges of the traditional Jump Point Search(JPS)in mobile robot path planning.These challenges include excessive no...This paper introduces an Improved Bidirectional Jump Point Search(I-BJPS)algorithm to address the challenges of the traditional Jump Point Search(JPS)in mobile robot path planning.These challenges include excessive node expansions,frequent path inflexion points,slower search times,and a high number of jump points in complex environments with large areas and dense obstacles.Firstly,we improve the heuristic functions in both forward and reverse directions to minimize expansion nodes and search time.We also introduce a node optimization strategy to reduce non-essential nodes so that the path length is optimized.Secondly,we employ a second-order Bezier Curve to smooth turning points,making generated paths more suitable for mobile robot motion requirements.Then,we integrate the Dynamic Window Approach(DWA)to improve path planning safety.Finally,the simulation results demonstrate that the I-BJPS algorithm significantly outperforms both the original unidirectional JPS algorithm and the bidirectional JPS algorithm in terms of search time,the number of path inflexion points,and overall path length,the advantages of the I-BJPS algorithm are particularly pronounced in complex environments.Experimental results from real-world scenarios indicate that the proposed algorithm can efficiently and rapidly generate an optimal path that is safe,collision-free,and well-suited to the robot’s locomotion requirements.展开更多
Various fishery information systems have been developed in different times and on different platforms. Wet） service application composition is crucial in the sharing and integration of fishery data and information. I...Various fishery information systems have been developed in different times and on different platforms. Wet） service application composition is crucial in the sharing and integration of fishery data and information. In the present paper, a heuristic web service composition method based on fishery ontology is presented, and the proposed web services are described. Ontology reasoning capability was applied to generate a service composition graph. The heuristic function was introduced to reduce the searching space. The experimental results show that the algorithm used considers the services semantic similarity and adiusts web service composition plan by dynamically relying on the empirical data.展开更多
The ant colony optimization algorithm has been widely studied and many important results have been obtained.Though this algorithm has been applied to many fields,the analysis about its convergence is much less,which w...The ant colony optimization algorithm has been widely studied and many important results have been obtained.Though this algorithm has been applied to many fields,the analysis about its convergence is much less,which will influence the improvement of this algorithm.Therefore,the convergence of this algorithm applied to the traveling salesman problem(TSP)was analyzed in detail.The conclusion that this algorithm will definitely converge to the optimal solution under the condition of 0<q_(0)<1 was proved true.In addition,the influence on its convergence caused by the properties of the closed path,heuristic functions,the pheromone and q_(0) was analyzed.Based on the above-mentioned,some conclusions about how to improve the speed of its convergence are obtained.展开更多
文摘The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.
基金supported by the Xinjiang Uygur Autonomous Region Central Guided Local Science and Technology Development Fund Project(No.ZYYD2025QY17).
文摘This paper introduces an Improved Bidirectional Jump Point Search(I-BJPS)algorithm to address the challenges of the traditional Jump Point Search(JPS)in mobile robot path planning.These challenges include excessive node expansions,frequent path inflexion points,slower search times,and a high number of jump points in complex environments with large areas and dense obstacles.Firstly,we improve the heuristic functions in both forward and reverse directions to minimize expansion nodes and search time.We also introduce a node optimization strategy to reduce non-essential nodes so that the path length is optimized.Secondly,we employ a second-order Bezier Curve to smooth turning points,making generated paths more suitable for mobile robot motion requirements.Then,we integrate the Dynamic Window Approach(DWA)to improve path planning safety.Finally,the simulation results demonstrate that the I-BJPS algorithm significantly outperforms both the original unidirectional JPS algorithm and the bidirectional JPS algorithm in terms of search time,the number of path inflexion points,and overall path length,the advantages of the I-BJPS algorithm are particularly pronounced in complex environments.Experimental results from real-world scenarios indicate that the proposed algorithm can efficiently and rapidly generate an optimal path that is safe,collision-free,and well-suited to the robot’s locomotion requirements.
基金funded by the National High Technology Research and Development Program of China (2006AA10Z239)the Key Technologies R&D Program of China during the 11th Five-Year Plan period (2006BAD10A05)
文摘Various fishery information systems have been developed in different times and on different platforms. Wet） service application composition is crucial in the sharing and integration of fishery data and information. In the present paper, a heuristic web service composition method based on fishery ontology is presented, and the proposed web services are described. Ontology reasoning capability was applied to generate a service composition graph. The heuristic function was introduced to reduce the searching space. The experimental results show that the algorithm used considers the services semantic similarity and adiusts web service composition plan by dynamically relying on the empirical data.
基金supported by the National Natural Science Foundation of China (Grant No.60673102)the Natural Science Foundation of Jiangsu Province of China (Grant No.BK2006218).
文摘The ant colony optimization algorithm has been widely studied and many important results have been obtained.Though this algorithm has been applied to many fields,the analysis about its convergence is much less,which will influence the improvement of this algorithm.Therefore,the convergence of this algorithm applied to the traveling salesman problem(TSP)was analyzed in detail.The conclusion that this algorithm will definitely converge to the optimal solution under the condition of 0<q_(0)<1 was proved true.In addition,the influence on its convergence caused by the properties of the closed path,heuristic functions,the pheromone and q_(0) was analyzed.Based on the above-mentioned,some conclusions about how to improve the speed of its convergence are obtained.
