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检索条件"主题词=Artificial immune algorithm"

共 158 条记录，以下是31-40 订阅

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A novel artificial immune algorithm applied to solve optimization problems

A novel artificial immune algorithm applied to solve optimiz...

引用

8th International Conference on Control, Automation, Robotics and Vision (ICARCV 2004)

作者： Li, CH Zhu, YF Mao, ZY S China Univ Technol Coll Automated Sci & Engn Guangzhou 510640 Peoples R China

ISBN: (纸本)0780386531

In the paper, we discuss multi-objective (MO) optimization problems solved by artificial immune algorithm. We present a novel artificial immune algorithm for MO optimization (AIAMOO) and analyze its powerful performance from the immune system point of view. Finally, the AIAMOO is applied to solve two complex MO optimization problems and the results can perfectly map the Pareto-optimal front. It shows the good prospect to apply artificial immune system to solve MO optimization problems.

关键词： multi-objective optimization artificial immune algorithm evolutionary algorithm

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Fault Diagnosis of Gearbox by Selective Ensemble Learning Based on artificial immune algorithm 3

Fault Diagnosis of Gearbox by Selective Ensemble Learning Ba...

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3rd International Conference on Systems and Informatics (ICSAI)

作者： Liu, Tianyu Shanghai Dianji Univ Sch Elect Shanghai Peoples R China

ISBN: (纸本)9781509055210

Because faults of gearbox are one of the most important factors of wind turbine, it is very important to research gearbox fault diagnosis technology. The problem of class unbalance is encountered in fault diagnosis of gearbox, which has a serious negative impact on the performance of the classifier of the hypothetical class. While it is critical that previous work rarely pays attention to the problem of gearbox fault diagnosis in this class imbalance. In the problem of imbalance, some features of dataset are superfluous, even irrelevant. These characteristics will affect the generalization performance of the learning machine. Here, it is propose AIEE (based on artificial immune algorithm function selection Easy Ensemble) to improve the gearbox fault diagnosis class imbalance problem. The experimental results of UCI datasets and gearbox fault data sets shows that AIEE algorithm can improve the classification performance and prediction accuracy of unbalanced datasets.

关键词： fault diagnosis artificial immune algorithm Selective ensemble learning algorithm Support vector machines Bagging

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Two level optimization model of construction safety for prefabricated construction and its artificial immune algorithm 30

Two level optimization model of construction safety for pref...

引用

30th Chinese Control and Decision Conference (CCDC)

作者： Chang Chunguang Wang Jiayuan Shenyang Jianzhu Univ Sch Management Shenyang 110168 Peoples R China

ISBN: (纸本)9781538612446

To improve the safety management performance of prefabricated construction (PC), the optimization problem of construction safety for PC is studied. A frame of two level optimization model of construction safety for PC is proposed, and the two level optimization models are established by mathematic programming theory. In the first level optimization model, the objective function is maximizing the level of safety management of PC. The constraints include the sum limit of each cost item during each stage, the resource sum limit for the project. In the second level optimization model, the objective function is maximizing the safety degree of prefabricated component installation. The constraints include the workload limit of per level workers, the expenditure limit for the direct installation of labor costs for prefabricated components, the workload ratio limit among varied level workers. The first level optimization model of construction safety for PC is solved by Simple Method, and the second level optimization model of construction safety for PC is solved by artificial immune algorithm. Above model and its solving algorithm can improve the precision of safety management for PC.

关键词： Prefabricated construction (PC) Two level Optimization model Safety management artificial immune algorithm

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An artificial immune algorithm for Minimal Steiner Tree Problems

An Artificial Immune Algorithm for Minimal Steiner Tree Prob...

引用

International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Gao, Yan-Ping Yang, Zong-Xiao Henan Univ Sci & Technol Informat Engn Coll 263 Kaiyuan Rd Luoyang 471023 Peoples R China Henan Univ Sci & Technol Inst Syst Sci & Engn Luoyang 471003 Peoples R China

ISBN: (纸本)9781479925186;9781479925193

The Minimum Steiner tree (MST) problem in the Euclidean plane is an nonlinear programming hard (NP-hard) problem, polynomial time algorithm is absent for solving the MST for a group of arbitrary terminal points, and the most difficulty is how to determine the position and number of Steiner points. A new method to solve MST problem by using an artificial immune algorithm was proposed in this paper. According to the breadth - first traversal sequence of minimum spanning tree, the terminal points can be divided into different convex hull sets, and the full Steiner tree (FST, named by Melzak) can be structured from the convex hull. The Steiner points can be vaccinated to minimum spanning tree as a vaccine, and the shortest length of the tree is the solution of MST. The average optimization effect of artificial immune algorithm is shorter 5.3% than the minimum spanning, and the performance of algorithm is remarkable and outstanding effectively with some engineering examples.

关键词： Minimum Steiner tree artificial immune algorithm Combinatorial optimization Vaccine

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Rule extraction of fault diagnose based on a Modified artificial immune algorithm

Rule extraction of fault diagnose based on a Modified artifi...

引用

6th International Symposium on Instrumentation and Control Technology

作者： Hao Xiaoli Xie Keming Taiyuan Technol Univ Taiyuan 030024 Shanxi Peoples R China

ISBN: (纸本)081946452X

When employed in fault diagnosis, rough set can realize attribution reduction. But it can not discrete attribution and reduct attribution simultaneously, therefore we can not say that it can automatically extract rules. To solve the problem, a new rule extraction method based on developed artificial immune algorithm is firstly proposed in the paper. At first, a new method of encoding is produced which can make the process of discretion and reduction unify. Secondly, a new definition of concentration of antibodies not only compare individuals in structure and space, but also in fitness value. Thirdly, the algorithm provide dissimilation operator and similar-taxis operator, which replace choice, expansion and mutation in traditional artificial immune algorithm. All these developments not only maintain diversity of the antibody population, but also converge faster. Finally, we apply the algorithm to fault diagnose of heat recoup system in steam turbine. Tests proved that the algorithm is feasible, and the diagnose rules acquired by the algorithm have higher accuracy rate.

关键词： artificial immune algorithm fault diagnose rule extraction steam turbine

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Application of artificial immune algorithm in e-commerce oriented negotiation support system

Application of artificial immune algorithm in e-commerce ori...

引用

International Conference on Machine Learning and Cybernetics

作者： Wang, H Li, YJ Feng, YQ Li, JF Xie, AS Harbin Inst Technol Sch Management Harbin 150001 Peoples R China

ISBN: (纸本)0780378652

Negotiation support system has become increasingly important since the advent of electronic commerce. But the existing NSS cannot conveniently, timely and effectively help negotiators make decisions in the real-time bargaining. Since immune algorithms have the advantages of converging global search space fast, intrinsic parallelism and resolving. the optimization problems with simulating the immune system, in this paper we attempt to apply artificial immune algorithm to providing solution supporting in the electronic commerce oriented NSS in order to offer optimal or near-optimal solutions for negotiators. We verify the feasibility and special superiority of this method through theory analysis and experiments.

关键词： negotiation support system (NSS) artificial immune algorithm electronic commerce

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Path Tracking of a Two-Wheeled Self-Balancing Robot Based on Multi-objective Optimization with artificial immune algorithm 7

Path Tracking of a Two-Wheeled Self-Balancing Robot Based on...

引用

7th International Conference on Robotics and Automation Sciences (ICRAS)

作者： Wang, Jiayuan Wuhan Univ Technol Sch Int Educ Wuhan Peoples R China

ISBN: (纸本)9798350313567

In this paper, a multi-objective optimization-based path tracking method for a two-wheeled self-balancing robot (TWSBR) is proposed. First, the dynamics model of the system is established based on the Newton-Euler method and simulated in simulink. Then an artificial immune algorithm is used to find the optimal motion parameters for each control point based on the parameter feedback of the TWSBR, and finally a proportional-integral-derivative controller (PID) is used for control. The advantages of this study are as follows: (1) The stability of the TWSBR in high-speed working condition is improved and the efficiency of the robot is enhanced by the optimization algorithm. (2) The anti-jamming capability of the TWSBR is improved through parameter feedback. (3) The optimized PID controller is used to control the motor torque, which avoids manual adjustment of parameters and improves the control efficiency. The method can be applied to TWSBR with fixed paths such as logistics distribution and space disinfection.

关键词： artificial immune algorithm two-wheeled self-balancing robot path tracking

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Mobile Robot Path Planning and Research in the Improved artificial immune algorithm

Mobile Robot Path Planning and Research in the Improved Arti...

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1st International Conference on Intelligent System and Applied Material (GSAM 2012)

作者： Hou, Yuanbin Wang, Wei Lu, Xiaoyue Xian Univ Sci & Technol Sch Elect & Control Engn Xian Peoples R China

ISBN: (纸本)9783037853689

Aim at local optimal problem in the path planning of mobile robot by artificial immune algorithm, it is proposed that the improved artificial immune algorithm of mobile robot path planning. Based on artificial immunity algorithm, the potential function method of an artificial potential field is used in this algorithm, improving randomness of the initial population of the artificial immune algorithm, then the algorithm make initial population turn to evolutionary operation through crossover, variance and selection operator to get optimum antibody. The simulation results showed that this algorithm is easy to get the optimal path, at the same time, increasing the speed of the path planning, and the length of the optimal path planning is less 28.5% compare with the traditional immune algorithm.

关键词： mobile robot path planning artificial immune algorithm field function immune evolutionary

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An artificial immune algorithm for Association Rule Mining among Concepts with Uncertainty 11

An Artificial Immune Algorithm for Association Rule Mining a...

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IEEE 11th International Colloquium on Signal Processing & its Applications (CSPA)

作者： Di, Hongyu Wang, Sun'an Xi An Jiao Tong Univ Sch Mech Engn Xian Shaanxi Peoples R China

ISBN: (纸本)9781479982493

During a design procedure of association rule mining approach, there are two common issues: the transformation method from continuous quantitative attributes to qualitative concepts, and efficiency of data mining. In order to acquire association rules in a database with different types of attributes, the cloud transformation which is included in the cloud model theoretical framework is applied as an uncertain concept extraction tool in this paper. By the feature analysis of association rule mining in uncertain concept space, the frequent item-set generation is converted to a combination optimization problem. A modified object function and artificial immune algorithm for association rule mining are designed accordingly. A novel method of non-frequent item hyper set detection is introduced to reduce the number of database scanning and improve the efficiency. The numerical experiments show that the proposed algorithm can accomplish the association rule mining by global random search, with the robustness that the computational cost is insensitive with the variation of threshold parameters.

关键词： Association rule cloud model artificial immune algorithm non-frequent item hyper set

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Base Station Locations Optimization in LTE using artificial immune algorithm 10

Base Station Locations Optimization in LTE using Artificial ...

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10th International Symposium on Computational Intelligence and Design (ISCID)

作者： Li, Liangliang Ma, Baoluo Jia, Zhenhong Si, Yujuan Xinjiang Univ Coll Informat Sci & Engn Urumqi 830046 Peoples R China Jilin Univ Coll Commun Engn Changchun 130012 Jilin Peoples R China Jilin Univ Zhuhai Coll Dept Elect Informat Zhuhai 519041 Peoples R China

ISBN: (纸本)9781538636756

In order to reduce the cost of network construction, improve the network coverage and system capacity, a novel approach of artificial immune algorithm(AIA) to solve the base station(BS) placement problem in Long Term Evolution(LTE) network is proposed in this paper. The mathematical model of AIA for BS locations planning problem was designed. Selecting a set of BSs with the minimum numbers from the candidate BS sites, in order to reach the purpose of minimize the BS construction cost, maximize the network coverage and satisfy the quality of service. Simulated experimental results show that the proposed method can obtain higher network coverage with lower cost of construction. Besides, the convergence was improved obviously.

关键词： LTE network base station location artificial immune algorithm local search

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