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4th IEEE International Conference on E-Health and Bioengineering (EHB)

作者： Costin, Hariton Bejinariu, Silviu Ioan Grigore T Popa Univ Med & Pharm Fac Med Bioengn Iasi Romania Romanian Acad Inst Comp Sci Iasi Romania

ISBN: (纸本)9781479923724

Medical signals are increasingly being used within healthcare for diagnosis, planning treatment, guiding treatment and monitoring disease evolution. Medical imaging mainly treats and processes missing, ambiguous, complementary, redundant, contradictory, distorted data, and information has a strong structural character. This paper reports two "immune algorithms" based approaches for medical signal processing. Immune algorithms belong to the Artificial Immune Systems field. The first proposed approach uses the clonal selection algorithm (CSA) for geometric transform estimation in image registration (IR). The second approach, the Dendritic Cell algorithm (DCA) is used for automatic driver stress detection using biomedical signals.

关键词： image registration artificial immune systems dendritic cells algorithms clonal selection algorithm

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Interference suppression of linear antenna arrays by phase-only control using a clonal selection algorithm

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2008年第3期345卷 254-266页

作者： Guney, K. Babayigit, B. Akdagli, A. Erciyes Univ Dept Elect & Elect Engn TR-38039 Kayseri Turkey Erciyes Univ Dept Comp Engn TR-38039 Kayseri Turkey

In this paper, an efficient technique based on clonal selection algorithm (clonalG) for linear antenna array pattern synthesis with null steering by controlling only the element excitation phases is presented. The clonalG is an evolutionary computation method inspired by the clonal selection principle of human immune system. To show the versatility and flexibility of the proposed clonalG, some examples of Chebyshev array pattern with the imposed single, multiple and broad nulls are given. The sensitivity of the nulling patterns due to small variations of the element phases is also investigated. (C) 2007 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： linear antenna arrays pattern nulling phase-only control clonal selection algorithm

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An expanded lateral interactive clonal selection algorithm and its application

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2008年第8期E91A卷 2223-2231页

作者： Gao, Shangce Dai, Hongwei Zhang, Jianchen Tang, Zheng Toyama Univ Fac Engn Toyama 9308555 Japan

Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.

关键词： clonal selection algorithm somatic hypermutation receptor editing idiotype traveling salesman problem

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Improved clonal selection algorithm combined with ant colony optimization

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2008年第6期E91D卷 1813-1823页

作者： Gao, Shangce Wang, Wei Dai, Hongwei Li, Fangjia Tang, Zheng Toyama Univ Fac Engn Toyama 9308555 Japan

Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit and explore the solution space parallely and effectively. However, it can not use enough environment feedback information and thus has to do a large redundancy repeat during search. On the other hand, ACO is based on the concept of indirect cooperative foraging process via secreting pheromones. Its positive feedback ability is nice but its convergence speed is slow because of the little initial pheromones. In this paper, we propose a pheromone-linker to combine these two algorithms. The proposed hybrid clonal selection and ant colony optimization (CSA-ACO) reasonably utilizes the superiorities of both algorithms and also overcomes their inherent disadvantages. Simulation results based on the traveling salesman problems have demonstrated the merit of the proposed algorithm over some traditional techniques.

关键词： clonal selection algorithm ant colony optimization traveling salesman problem hybridization

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A clonal selection algorithm Based Optimal Iterative Learning Control algorithm

A Clonal Selection Algorithm Based Optimal Iterative Learnin...

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7th World Congress on Intelligent Control and Automation

作者： Li, Hengjie Hao, Xiaohong Zhang, Lei Lanzhou Univ Technol Sch Elect & Informat Engn Lanzhou 730050 Gansu Peoples R China

ISBN: (纸本)9781424421138

Improved clonal selection algorithms were proposed as a method to implement optimal iterative learning control algorithms. The strength of the method is that it not only can cope with non-minimum phase plants and nonlinear plants even there are uncertainties in their models, but also can deal with constraints on input signals conveniently by a specially designed mutation operator. Simulations show that the convergence speed is satisfactory regardless of the nature of the plants and whether or not the models of the plants are precise.

关键词： clonal selection algorithm iterative learning control on-minimum phase plants nonlinear plants constraints

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A Novel FIR Filter Design Based on clonal selection algorithm

A Novel FIR Filter Design Based on Clonal Selection Algorith...

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7th International Symposium on Instrumentation and Control Technology

作者： Qiusheng Wang Shaokun Gao Jingpo Zhao Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

ISBN: (纸本)9780819473622

FIR filter has some advantages, such as system stability, simple implement, and linear phase. It has been widely used in digital signal processing and other relative fields. clonal selection algorithm has been applied successfully in solving problems like memory acquisition, multi-modal optimization and traveling salesman problem. This paper proposes a novel FIR filter design method. It combines clonal selection algorithm and window function method to achieve optimization. In the design process, float coding is adopted to increase the convergence precision. Some simulation experiments are carried out to verify the performance of the presented algorithm. The results show that the introduced method is able to design some FIR filter which is difficult for other methods. The filter design approach discussed in this paper is universal and easy to implement.

关键词： clonal selection algorithm FIR filter window function

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An artificial immune system based algorithm to solve unequal area facility layout problem

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EXPERT SYSTEMS WITH APPLICATIONS 2012年第5期39卷 5384-5395页

作者： Ulutas, Berna Haktanirlar Kulturel-Konak, Sadan Eskisehir Osmangazi Univ Dept Ind Engn TR-26480 Meselik Eskisehir Turkey Penn State Berks Management Informat Syst Reading PA 19610 USA

This study introduces an artificial immune system (AIS) based algorithm to solve the unequal area facility layout problem (FLP) with flexible bay structure (FBS). The proposed clonal selection algorithm (CSA) has a new encoding and a novel procedure to cope with dummy departments that are introduced to fill the empty space in the facility area. The algorithm showed consistent performance for the 25 test problem cases studied. The problems with 100 and 125 were studied with FBS first time in the literature. CSA provided four new best FBS solutions and reached to sixteen best-so-far FBS solutions. Further, the two very large size test problems were solved first time using FBS representation, and results significantly improved the previous best known solutions. The overall results state that CSA with FBS representation was successful in 95.65% of the test problems when compared with the best-so-far FBS results and 90.90% compared with the best known solutions that have not used FBS representation. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Artificial immune system clonal selection algorithm Unequal area facility layout problem Flexible bay structure

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Damage Identification of Steel Beams Using Local and Global Methods

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ADVANCES IN STRUCTURAL ENGINEERING 2012年第5期15卷 807-824页

作者： Wang, Ying Hao, Hong Deakin Univ Sch Engn Geelong Waurn Ponds Campus Geelong Vic 3216 Australia Univ Western Australia Sch Civil & Resource Engn Nedlands WA 6009 Australia

Structural condition monitoring methods can be generally classified as local and global. While the global method needs only a small number of sensors to measure the low-frequency structural vibration properties, the acquired information is often not sufficiently sensitive to minor damages in a structure. Local methods, on the other hand, could be very sensitive to minor damages but their detection range is usually small. To overcome the drawbacks and take advantage of both methods, an integrated condition monitoring system has been recently developed for structural damage detection, which combines guided wave and structural vibration tests. This study aims at finding a viable damage identification method for steel structures by using this system. First, a spectral element modelling method is developed, which can simulate both wave propagation and structural vibration properties. Then the model is used in updating analysis to identify crack damage. Extensive numerical simulations and model updating works are conducted. The experimental and numerical results suggest that simply combining the objective functions cannot provide better structural damage identification. A two-stage damage identification scheme is more suitable for identifying damage in steel beams.

关键词： damage identification vibration wave propagation spectral element method model updating clonal selection algorithm

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Particle swarm optimization based feedforward controller for a XY PZT positioning stage

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MECHATRONICS 2012年第5期22卷 614-628页

作者： Lin, Chih-Jer Lin, Po-Ting Natl Taipei Univ Technol Grad Inst Automat Technol Taipei 10608 Taiwan

Compensations for cross-axis coupling effect and hysteretic nonlinearity of a novel XY piezo-actuated positioning stage are presented in this study. The piezo-actuated stage utilizes a monolithic flexure-based mechanism (FBM) to achieve translations in X- and Y-axes instead of using stacked mechanisms. A hysteresis model with crossover term is proposed to alleviate the cross coupling effect between X- and Y-stages during precision positioning tasks. System identifications using real-coded genetic algorithm (RCA) and clonal selection algorithm (CSA) are compared with particle swarm optimization (PSO). The results show that PSO provides better performance than the others. Therefore, a feedforward controller with cross-axis coupling compensation is studied and the used for the piezo-actuated FBM to enhance the precision of the coarse positioning stage. The experimental results confirm that the proposed controller can achieve precision tracking tasks with submicron precision. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Piezoelectric actuator Flexure-based mechanism Real-coded genetic algorithm clonal selection algorithm Particle swarm optimization System identification

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Short-term hydrothermal scheduling using Gravitational Search algorithm

Short-term hydrothermal scheduling using Gravitational Searc...

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2nd International Conference on Power, Control and Embedded Systems (ICPCES)

作者： Barisal, A. K. Sahu, N. C. Prusty, R. C. Hota, P. K. Veer Surendra Sai Univ Technol Dept Elect Engn Burla Orissa India ITER Dept Elect Engn Bhubaneswar Orissa India Coll Engn & Technol Bhubaneswar Orissa India

ISBN: (纸本)9781467310499;9781467310475

The Gravitational Search algorithm (GSA) is one of the recent additions to the new heuristic optimization algorithms based on law of gravity and mass interactions has been applied to solve the short term scheduling hydrothermal system. In the proposed algorithm, the searcher agents are collection of masses interact with each other based on the Newtonian gravity and the laws of motion. Hydrothermal scheduling involves the optimization of nonlinear objective function with set of operational and physical constraints. The cascading nature of hydro plants, water transport delay and scheduling time linkage, power balance constraints, variable hourly water discharge limits, reservoir storage limits, operation limits of thermal and hydro units, hydraulic continuity constraint and initial and final reservoir storage limits are fully taken into consideration. The validity and the performance of the proposed approach are demonstrated through a large hydrothermal test system comprising of 54 thermal and 44 hydro plants.

关键词： clonal selection algorithm gravitational search algorithm heuristic algorithm hydrothermal scheduling

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