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Optimized k-nearest neighbors for classification of prosthetic hand movements using electromyography signal

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 133卷

作者： Sahu, Padmini Singh, Bikesh Kumar Nirala, Neelamshobha Natl Inst Technol Raipur Dept Biomed Engn Raipur India

Electromyography (EMG) signals are essential, as they are used to measure muscular activity in different parts of the human body. The measurement and analysis of EMG signal lead to various applications of muscle disorders such as muscular dystrophy, myopathy, hand movements, etc. In this paper, an improved and effective hand movement classification model is developed for amputee subjects. It includes: (1) EMG feature extraction using Discrete Wavelet Transform (DWT), (2) EMG feature selection using binary Global Best Guided Gaussian Artificial Bee Colony (BGGABC), (3) Hand movements classification using Optimized k -nearest neighbors (OKNN) classifier. The EMG signal is taken from the DB3 of NinaPro dataset comprising 17 different prosthetic hand movements recorded from 11 amputee subjects. Thereafter, DWT is applied to decompose the EMG signal for extracting features. An improved wrapper -based feature selection technique (BGGABC) is used to select the optimal feature subset for effective classification. The two variants of KNN, i.e. Smallest Modified KNN and Largest Modified KNN are taken in which item strength to a class is optimized for efficient classification. The strength of an item to a class depends on distance and weight of an item to a class. Therefore, a multi -objective non -dominated sorting genetic algorithm -ii (NSGA-ii) is used for optimizing these two contradictory parameters (distance and weight) simultaneously to have optimized variants, namely: Optimized Smallest KNN (OSKNN) and Optimized Largest KNN (OLKNN). Extensive results show that the proposed method OKNN achieved the highest classification accuracy of 93.07% (OLKNN) and 89.43% (OSKNN) compared with KNN variants and competitors.

关键词： Electromyography Discrete wavelet transform GlobaL Best Guided Gaussian Artificial Bee Colony K-nearest neighbors non-dominated sorting genetic algorithm-ii

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Design, control and optimization of multi-degree-of-freedom spherical induction motor

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2022年第2期236卷 778-794页

作者： Liu, Ping Deng, Tao Su, Zhenhua Jiang, Lu Ding, Zhentao Chongqing Jiaotong Univ Sch Aeronaut 66 Xuefu Rd Chongqing 400074 Peoples R China Chongqing Jiaotong Univ Green Aerotech Res Inst Chongqing Peoples R China Chongqing Jiaotong Univ Sch Mechatron & Vehicle Engn Chongqing Peoples R China

In order to meet the requirements of multi-degree-of-freedom (multi-DOF) driving units for omnidirectional vehicle wheels, a multi-DOF spherical induction motor (SIM) is proposed with composite rotor through the conversion of design concept of linear induction motor (LIM), which compensates for the insufficiency of traditional multi-DOF driving scheme with structural complexity, control difficulties and poor dynamic performance. The SIM realizes two DOF driving and has the characteristics of direct output on rotor surface. Firstly, the overall design of SIM is drafted, as well as finite element model and control system are established. Subsequently, in order to optimize SIM performance, the multi-objective optimization design of composite rotor structure is proposed by adopting non-dominated sorting genetic algorithm-ii (NSGA-ii). The results show that the reasonable design of rotor structure can effectively improve output torque and reduce fluctuation. And the proposed design idea based on theory of LIM can provide a reference for SIM design.

关键词： Multi-degree-of-freedom multi-objective optimization non-dominated sorting genetic algorithm-ii spherical induction motor design

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The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-ii

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第9-12期70卷 2097-2109页

作者： Zhang, Guojun Zhang, Zhen Ming, Wuyi Guo, Jianwen Huang, Yu Shao, Xinyu Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Tech Wuhan 430074 Peoples R China

In the medium-speed wire electrical discharge machining (MS-WEDM) process, the extremely high temperature and massive electrical discharges in a fraction of 1 s result in the poor surface quality such as high tensile residual stresses, high surface roughness, white layers, and micro cracks. In this paper, an experimental plan for central composite design (CCD) of processing the tool steel (SKD11) has been conducted according to response surface methodology (RSM). The aim is to develop the mathematical model that can correlate the main process parameters of MS-WEDM with machining performance and to seek the optimal parameters on material removal rate (MRR) and 3D surface quality (Sq) by integrated RSM and non-dominated sorting genetic algorithm-ii (NSGA-ii). Then, a set of pareto-optimal solutions is obtained. Moreover, from the confirmation experiment, it has been proved that the optimal process-parameter combinations are suitable on the MRR and the 3D surface texture. Eventually, it has also demonstrated that the method of integrated RSM and NSGA-ii is an effective way for multi-objective optimization.

关键词： Multi-objective Optimization Response surface methodology non-dominated sorting genetic algorithm-ii WEDM Material removal rate 3D surface quality

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Multi-Objective Multi-Index Transportation Model for Crude Oil Using Fuzzy NSGA-ii

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第2期23卷 1347-1356页

作者： Latpate, Raosaheb Kurade, Sandesh S. Savitribai Phule Pune Univ Dept Stat Pune 411007 Maharashtra India Savitribai Phule Pune Univ Ctr Adv Studies Pune 411007 Maharashtra India MES Abasaheb Garware Coll Dept Stat Pune 411004 Maharashtra India

The import and export of crude oil are vastly affected by the economy of a developing country. It can be useful for the production of petroleum products. Likewise, the developing country, India is completely relying on the import of crude oil from Gulf countries. Thus, there is a need for optimization of routes and modes of transportation. This article presents a two-stage cost and time minimizing fuzzy business restricted multi-objective multi-index transportation problem, in which supplies, demands, and requirements are triangular fuzzy numbers. A business restricted constraints using binary variables are added in the developed supply chain of crude oil in India. The proposed model helps the decision-maker to choose the source country for the import of crude oil. The model is solved by using our proposed fuzzy non-dominated sorting genetic algorithm (NSGA)-ii. The performance of the proposed algorithm is analyzed by using a simulation technique for uncertainty level alpha is an element of [0, 1]. Also, the Pareto decision space for formulated business restricted transportation problem is discussed using alpha-cut technique. For the superiority of the proposed methodology, we have implemented this on real-world case study viz., Daya case study. Based on the results we claim that the methodology is superior.

关键词： Crude oil multi-objective multi-index non-dominated sorting genetic algorithm-ii supply chain transportation problem triangular fuzzy number

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A multi-criteria optimization technique for SSSC based power oscillation damping controller design

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AIN SHAMS ENGINEERING JOURNAL 2016年第2期7卷 553-565页

作者： Swain, Sarat Chandra Panda, Sidhartha Mahapatra, Srikanta KIIT Univ Dept Elect Engn Bhubaneswar Odisha India VSSUT Dept Elect Engn Burla Odisha India

In this paper, non-dominated sorting genetic algorithm-ii (NSGA-ii) technique is applied to obtain Pareto optimal set of solutions pertaining to the tuning of lead-lag structured SSSC-based stabilizer. The design objective is to get maximum damping (performance) with minimum control effort (cost). Further a fuzzy based membership function value assignment method is employed to choose the best compromise solution. Simulation results are presented under various loading conditions and disturbances for various control signals to show the effectiveness and robustness of the proposed approach. The effectiveness and superiority of the proposed design approach are illustrated for both single machine infinite bus and multi-machine power systems by comparing the proposed approach with some recently published single objective and evolutionary multi-objective approaches such as Differential Evolution (DE), Particle Swarm Optimization (PSO) and Multi-objective genetic algorithm. It is observed that the proposed approach yields superior damping performance compared to some recently published approaches. (C) 2015 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V.

关键词： Power system stability Multi-criteria optimization Pareto optimal set Static synchronous series compensator non-dominated sorting genetic algorithm-ii

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Multi-objective hydraulic optimization and analysis in a minipump

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Science Bulletin 2015年第17期60卷 1517-1526页

作者： Bin Duan Minqing Luo Chao Yuan Xiaobing Luo School of Energy and Power Engineering Huazhong University of Science and Technology

Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characterize and optimize a particular mechanical minipump. The optimization work was conducted to cope with the conflict between pressure head and hydraulic efficiency by an improved back-propagation neural network （BPNN） with the non-dominated sorting genetic algorithm-ii （NSGA-ii）. The improved BPNN was utilized to predicate hydraulic performance and, moreover, was modified to improve the prediction accuracy. The NSGA-ii was processed for minipump multi-objective optimization which is dominated by four impeller dimensions. During hydraulic optimization, the processing feasibility was also taken into consideration. Experiments were conducted to validate the above optimization methods. It was proved that the optimized minipump was improved by about 24 % in pressure head and 4.75 % in hydraulic efficiency compared to the original designed prototype. Meanwhile, the sensitivity test was used to analyze the influence of the four impeller dimensions. It was found that the blade outlet angle β2 and the impeller inlet diameter Do significantly influence the pressure head H and the hydraulic efficiency η, respec- tively. Detailed internal flow fields showed that the optimum model can relieve the impeller wake and improve both the pressure distribution and flow orientation.

关键词： Minipump Optimization Back-propagation neural network non-dominated sorting genetic algorithm-ii

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Selection of optimal process parameters in WEDM while machining Al7075/SiCp metal matrix composites

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第1-4期73卷 299-314页

作者： Rao, Thella Babu Krishna, A. Gopala GITAM Univ Dept Mech Engn Visakhapatnam 502329 Andhra Pradesh India Jawaharlal Nehru Technol Univ Univ Coll Engn Dept Mech Engn Kakinada 533003 Andhra Pradesh India

Aluminium metal matrix composites (MMCs) reinforced with silicon carbide particulate (SiCp) find several applications due to their improved mechanical properties over the conventional metals for a wide variety of aerospace and automotive applications. However, the presence of discontinuously distributed hard ceramic in the MMCs made them as difficult-to-cut materials for conventional machining methods. The wire electrical discharge machining (WEDM), as a widely adopted non-traditional machining method for difficult-to-cut precision components, found an appropriate metal removal process for MMCs to enhance quality of cut within the stipulated cost. While machining the advanced materials like MMCs, a clear understanding into the machining performance of the process for its control variables could make the process uncomplicated and economical. In light of the growing industrial need of making high performance-low cost components, the investigation aimed to explore the machining performance characteristics of SiCp reinforced Al7075 matrix composites (Al7075/SiCp) during WEDM. While conducting the machining experiments, surface roughness, metal removal rate, and wire wear ratio are considered the responses to evaluate the WEDM performance. Response surface methodology is used to develop the empirical models for these WEDM responses. SiC particulate size and volume percentages are considered the process variables along with pulse-on time, pulse-off time, and wire tension. Analysis of variance (ANOVA) is used to check the adequacy of the developed models. Since the machining responses are conflicting in nature, the problem is formulated as a multi-objective optimization problem and is solved using the non-dominated sorting genetic algorithm-ii to obtain the set of Pareto-optimal solutions. The derived optimal process responses are confirmed by the experimental validation tests, and the results are analyzed by SEM.

关键词： Al7075/SiCp Stir casting WEDM non-dominated sorting genetic algorithm-ii

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A Modified micro genetic algorithm for undertaking Multi-Objective Optimization Problems

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2013年第3期24卷 483-495页

作者： Tan, Choo Jun Lim, Chee Peng Cheah, Yu-N Univ Sci Malaysia Sch Comp Sci George Town Malaysia Deakin Univ Ctr Intelligent Syst Res Burwood Vic Australia

In this paper, a Modified micro genetic algorithm (MmGA) is proposed for undertaking Multi-objective Optimization Problems (MOPs). An NSGA-ii inspired elitism strategy and a population initialization strategy are embedded into the traditional micro genetic algorithm (mGA) to form the proposed MmGA. The main aim of the MmGA is to improve its convergence rate towards the pareto optimal solutions. To evaluate the effectiveness of the MmGA, two experiments using the Kursawe test function in MOPs are conducted, and the results are compared with those from other approaches using a multi-objective evolutionary algorithm indicator, i.e. the Generational Distance (GD). The outcomes positively demonstrate that the MmGA is able to provide useful solutions with improved GD measures for tackling MOPs.

关键词： Multi-objective optimisation micro genetic algorithm non-dominated sorting genetic algorithm-ii elitism strategy population initialisation strategy

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Solving multi-objective water management problems using evolutionary computation

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2017年第Part1期204卷 179-188页

作者： Lewis, A. Randall, M. Griffith Univ Inst Integrated & Intelligent Syst Nathan Qld Australia Bond Univ Bond Business Sch Southport Qld Australia

Water as a resource is becoming increasingly more valuable given the changes in global climate. In an agricultural sense, the role of water is vital to ensuring food security. Therefore the management of it has become a subject of increasing attention and the development of effective tools to support participative decision-making in water management will be a valuable contribution. In this paper, evolutionary computation techniques and Pareto optimisation are incorporated in a model-based system for water management. An illustrative test case modelling optimal crop selection across dry, average and wet years based on data from the Murrumbidgee Irrigation Area in Australia is presented. It is shown that sets of trade-off solutions that provide large net revenues, or minimise environmental flow deficits can be produced rapidly, easily and automatically. The system is capable of providing detailed information on optimal solutions to achieve desired outcomes, responding to a variety of factors including climate conditions and economics. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Water resource management Multi-objective optimisation Evolutionary computation non-dominated sorting genetic algorithm-ii Pareto optimisation

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Supervised leukocyte segmentation in tissue images using multi-objective optimization technique

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2014年 31卷 44-52页

作者： Saraswat, Mukesh Arya, K. V. ABV Indian Inst Informat Technol & Management Gwa Gwalior India

Automated leukocytes segmentation in skin section images can be utilized by various researchers in animal experimentation for testing anti-inflammatory drugs and estimating dermatotoxicity of various toxic agents. However, complex morphological structure of skin section degrades the performance of leukocytes segmentation due to the extraction of vast number of artifacts/noise along with leukocytes. Rare works have been done to reduce such artifacts. Therefore, in this paper, a supervised methodology for leukocytes segmentation from the images of inflamed mice skin sections is introduced. The method is based on threshold based binary classifier to reduce the artifacts. The optimum values of thresholds are calculated using multi-objective optimization technique, non-dominated sorting genetic algorithm-ii (NSGA-ii) and receiver operating characteristic (ROC) curve. The experimental results confirm that the proposed method is prompt and precise to segment the leukocytes in highly variable images. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Leukocyte segmentation non-dominated sorting genetic algorithm-ii Receiver operating characteristic curve Threshold

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