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Relevant bibliographies by topics / Taguchi's algorithm

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Academic literature on the topic 'Taguchi's algorithm'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Taguchi's algorithm"

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Marlan, Zulkifli Marlah, Khairur Rijal Jamaludin, Faizir Ramlie, and Nolia Harudin. "Taguchi's T-method with nearest integer-based binary bat algorithm for prediction." Bulletin of Electrical Engineering and Informatics 11, no. 4 (2022): 2215–24. http://dx.doi.org/10.11591/eei.v11i4.3859.

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Taguchi’s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi’s orthogonal array is utilized to determine a subset of significant features to be used in formulating the optimal prediction model. This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat opti

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Zaharis, Zaharias D. "A MODIFIED TAGUCHI'S OPTIMIZATION ALGORITHM FOR BEAMFORMING APPLICATIONS." Progress In Electromagnetics Research 127 (2012): 553–69. http://dx.doi.org/10.2528/pier12040108.

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Chow Yong Huan, Wan Zuki Azman Wan Muhamad, Zainor Ridzuan Yahya, Nor Hizamiyani Abdul Azziz, Tan Li Mei, and Tan Xiao Jian. "Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset." Journal of Advanced Research in Applied Sciences and Engineering Technology 31, no. 3 (2023): 93–105. http://dx.doi.org/10.37934/araset.31.3.93105.

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The Mahalanobis-Taguchi System (MTS) is a statistical approach used in breast cancer research to facilitate early detection and promote efficient treatment. The technique analyses mammogram images for significant features using a multivariate statistical analysis technique. It combines the Mahalanobis distance (MD) and Taguchi's method to determine the differences between benign and malignant samples. While orthogonal array (OA) has been widely used in MTS, it has been criticised for providing suboptimal results due to insufficient coverage of feature combinations during the feature optimisati

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Srivani Reddy. "Minimizing Localization error in Wireless sensor networks Taguchi method." Journal of Electrical Systems 20, no. 3 (2024): 4021–29. http://dx.doi.org/10.52783/jes.5407.

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Localization is a key research area in wireless sensor networks. The study focuses on the system's behavioral analysis in terms of minimizing localization error by adjusting parameters such as nodes, network size, communication range, and network deployment. Implementing the Kalman filter in the localization algorithm helps strengthen the technique and improve the success rate in the presence of measurement malfunctions. A series of trials were carried out to an optimal level utilizing the Taguchi technique to determine the most influential parameter among them. Taguchi's experimental research

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Moorthy, S. Srinivasa, K. Manonmani, and T. Elangovan. "An Optimization Approach to the Dry Sliding Wear Behavior of Particulate Filled Glass Fiber Reinforced Hybrid Composites." Journal of Engineered Fibers and Fabrics 10, no. 2 (2015): 155892501501000. http://dx.doi.org/10.1177/155892501501000213.

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The new set of hybrid composites consisting of randomly oriented short e glass fiber reinforcement, polyester resin and titanium oxide (TiO2) particulate were developed by hand layup technique. Wear test was carried out by rubber wheel abrasive test (RWAT) rig with the four operating variables filler content, applied load, abrasive grit size (Al2O3) and test duration. The wear test of the composites were done on the basis of Taguchi's L9 (34) Orthogonal array. Analysis of variance and S/N ratio was used to study the optimum wear. From, Taguchi's experimental design a mathematical regression mo

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Tang, Cheng-Yuan, Yi-Leh Wu, and Chien-Chin Peng. "Fundamental matrix estimation by multiobjective genetic algorithm with Taguchi's method." Applied Soft Computing 12, no. 1 (2012): 553–58. http://dx.doi.org/10.1016/j.asoc.2011.08.004.

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Ullah, Wasif, Mohd Fadzil Faisae Ab. Rashid, Muhammad Ammar Nik Mu’tasim, and Ghanshyam G. Tejani. "Minimizing Total Production Cost in Hybrid Flow Shop Scheduling using Taguchi Enhanced Particle Swarm Optimization Algorithm." Journal of Advanced Research Design 132, no. 1 (2025): 41–51. https://doi.org/10.37934/ard.132.1.4151.

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This study uses metaheuristic optimization algorithms to minimize the total production cost (TPC) in a hybrid flow shop scheduling (HFS) environment. Scheduling jobs in manufacturing systems is vital for fulfilling customer demands and improving efficiency. In this research, four well-established metaheuristic algorithms, namely Tuned Particle Swarm Optimization (TPSO), Standard particle swarm optimization (PSO), Sine cosine algorithm (SCA) and Arithmetic optimization algorithm (AOA), were explored for TPC optimization in HFS using MATLAB (2022b). Through experimental analysis, TPSO consistent

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Madhesan, Pradeep Kumar, Venkatesan Rajamanickam, and Manimurugan Manickam. "Optimization of process parameters in turning of magnesium AZ91D alloy for better surface finish using genetic algorithm." Acta Innovations, no. 43 (June 20, 2022): 54–62. http://dx.doi.org/10.32933/actainnovations.43.5.

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This research examined at the optimum cutting parameters for producing minimum surface roughness and maximum Material Removal Rate (MRR) when turning magnesium alloy AZ91D. Cutting speed (m/min), feed (mm/rev), and cut depth (mm) have all been considered in the experimental study. To find the best cutting parameters, Taguchi's technique and Response Surface Methodology (RSM), an evolutionary optimization techniques Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed. GA gives better results of 34.04% lesser surface roughness and 15.2% higher MRR values

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Yıldız, Ali Rıza. "A new design optimization framework based on immune algorithm and Taguchi's method." Computers in Industry 60, no. 8 (2009): 613–20. http://dx.doi.org/10.1016/j.compind.2009.05.016.

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Manogaran, Gnanasekaran, and Satheesh Anbalagan. "Investigation of turbulence characteristics and its influential parametric optimization of a double-sided lid-driven cavity using Taguchi and ANOVA methods." Thermal Science, no. 00 (2024): 56. http://dx.doi.org/10.2298/tsci230910056m.

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This paper investigates turbulence characteristics and the parameters controlling the turbulent incompressible flow of a double-sided lid-driven cavity. The effects of varying Reynolds numbers (1?104 ? Re ? 2?105), speed ratios (0.05 ? S ? 1.0), and aspect ratios (0.5 ? K ? 2.0) on the turbulent quantities, such as kinetic energy (k), dissipation (?), turbulent viscosity (?t) are analyzed. The k-? turbulence model equations are solved using the FVM-based SIMPLE algorithm. Taguchi's approach uses an L16 orthogonal array to determine the optimal cavity parameters. The significance of the conside

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Dissertations / Theses on the topic "Taguchi's algorithm"

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Rowlands, H. "Optimum design using the Taguchi method with neural networks and genetic algorithms." Thesis, Cardiff University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241701.

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Garzon, Inti Elias. "Optimisation for product and process improvement : investigation of Taguchi tools and genetic algorithms." Thesis, University of Newcastle Upon Tyne, 2000. http://hdl.handle.net/10443/471.

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Despite criticisms of its methodology, the Taguchi philosophy for quality improvement is generally applauded. Though originally intended to primarily achieve its results "off line", during the product design phase and before manufacturing, it has frequently also been deployed to solve problems "on line". Taguchi identifies the crucial design phases as "system design" and "parameter design", and his statistically-based tools are directed at the latter. The general objective of this investigation is to study two contrasting approaches to product and process optimisation, ie Genetic Algorithms, w

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Mahendra, Adhiguna. "Methodology of surface defect detection using machine vision with magnetic particle inspection on tubular material." Thesis, Dijon, 2012. http://www.theses.fr/2012DIJOS051.

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[...]L’inspection des surfaces considérées est basée sur la technique d’Inspection par Particules Magnétiques (Magnetic Particle Inspection (MPI)) qui révèle les défauts de surfaces après les traitements suivants : la surface est enduite d’une solution contenant les particules, puis magnétisées et soumise à un éclairage Ultra-Violet. La technique de contrôle non destructif MPI est une méthode bien connue qui permet de révéler la présence de fissures en surface d’un matériau métallique. Cependant, une fois le défaut révélé par le procédé, ladétection automatique sans intervention de l’opérateur

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Hizli, Cem. "Thermal Optimization of Veo+ Projectors (thesis work at Optea AB) : Trying to reduce noise of the Veo+ projector by DOE (Design of Experiment) tests to find anoptimal solution for the fan algorithm while considering the thermal specifics of the unit." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-10382.

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The Veo+ projector is using a cooling system that consists of fan and blowers. This system is cooling the electronic components of the device and the lamp of the projector, however extracting a high noise. To lower this noise the rpm speeds (rotational speed) of the fan and blowers should be decreased. Thus, lowering the speed will result in higher temperature values in whole system (inside the device). While lowering the speed, the higher temperature values should be kept within the thermal design specifications of the electronic components. The purpose of this thesis work is to find an optim

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Zadeh, Saman Akbar. "Application of advanced algorithms and statistical techniques for weed-plant discrimination." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2020. https://ro.ecu.edu.au/theses/2352.

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Precision agriculture requires automated systems for weed detection as weeds compete with the crop for water, nutrients, and light. The purpose of this study is to investigate the use of machine learning methods to classify weeds/crops in agriculture. Statistical methods, support vector machines, convolutional neural networks (CNNs) are introduced, investigated and optimized as classifiers to provide high accuracy at high vehicular speed for weed detection. Initially, Support Vector Machine (SVM) algorithms are developed for weed-crop discrimination and their accuracies are compared with a con

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Ittiwattana, Waraporn. "A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1030366020.

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Kang, Hong-ming, and 康宏銘. "Comparisons between Hybrid Taguchi-Genetic Algorithm and Traditional Genetic Algorithm." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/99259342073803393917.

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碩士<br>國立臺南大學<br>數位學習科技學系碩士班<br>99<br>Hybrid Taguchi genetic algorithm can be used to solve the global continuous optimization problems. Aside from the global search capability of traditional genetic algorithm, it further combines Taguchi experimental method to explore the optimal feasibility of the offspring. Taguchi method is inserted between the crossover and mutation operations of the traditional genetic algorithm. Hybrid Taguchi genetic algorithm also seems to outperform the traditional genetic method in obtaining the optional or near optimal solutions because of its fast convergence abili

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Chan, Hsiao-Ling, and 詹曉苓. "Optimizing Parameter Design for Taguchi's Dynamic Characteristics with Hybrid Algorithms." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/84426253274659971226.

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博士<br>國立交通大學<br>工業工程與管理系所<br>95<br>Parameter design is critical to enhancing a system’s robustness by identifying specific control factor and their levels that make the system less sensitive to noise. Most engineers applied Taguchi methods to optimize parameter design. However, Taguchi methods can only obtain the discrete optimal solution. They cannot identify the real optimum when the parameter values are continuous. The multi-response problem is too difficult to be considered by engineers with limited statistical knowledge. This research proposes a hybrid approach for combining neural networ

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Hsu, Song-Lin, and 許松麟. "Model Reduction Using Taguchi-Differential Evolution Algorithm." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/57441144799761042542.

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碩士<br>國立高雄第一科技大學<br>系統與控制工程研究所<br>95<br>In this thesis, the problems of model reduction are solved by using two improved differential evolution algorithms (DEA), which are called Taguchi-differential evolution algorithm (TDEA) and adjustable Taguchi-differential evolution algorithm（ATDEA）. The use of a reduced-order model makes it easier to implement analyses, simulations and control designs. The proposed TDEA is modified from the traditional DEA with mutation operation. The systematic reasoning ability of the Taguchi method can promote the mutation efficiency. The Taguchi method applied into

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Li, Kun-Chou, and 李坤洲. "Design of Digital IIR Filters Using Taguchi-Genetic Algorithm." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/68445580786363672020.

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碩士<br>國立高雄第一科技大學<br>機械與自動化工程所<br>92<br>The hybrid Taguchi-genetic algorithm (HTGA) approach is presented in this thesis to design digital IIR filters having equiripple behavior in both magnitude and group delay response. The proposed HTGA is modified from the traditional genetic algorithm(GA) with arithmetic crossover and non-uniform mutation. We apply Taguchi method to crossover and mutation operations. The systematic reasoning ability of the Taguchi method can promote the crossover efficiency and generate better offspring. The Taguchi method applied into mutation operations can enhance the n

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Book chapters on the topic "Taguchi's algorithm"

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Marlan, Zulkifli Marlah, Khairur Rijal Jamaludin, and Nolia Harudin. "Taguchi’s T-method with Normalization-Based Binary Bat Algorithm." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53960-2_27.

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Yildiz, Ali Rıza, and Ferruh Öztürk. "Hybrid Taguchi-Harmony Search Approach for Shape Optimization." In Recent Advances In Harmony Search Algorithm. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-04317-8_8.

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Tsai, C. F., C. G. D. Bowerman, J. I. Tait, and C. Bradford. "A Fuzzy Taguchi Controller to Improve Genetic Algorithm Parameter Selection." In Artificial Neural Nets and Genetic Algorithms. Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1_38.

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Bhati, Archana, Anil Kumar Baghel, and Barkha Singhal. "Optimization of Culture Conditions for EPS Production in Lactobacillus rhamnosus MTCC 5462 Through Taguchi Design Methodology." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1528-3_22.

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Ni, Yudong, Yuanyuan Li, and Yindong Shen. "An Improved Artificial Bee Colony Algorithm and Its Taguchi Analysis." In Communications in Computer and Information Science. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2829-9_11.

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Tsai, Ming-Tang. "Integrated Taguchi Method with Immune Algorithm for Solving Profit-Base Unit Commitment." In Lecture Notes in Electrical Engineering. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04573-3_1.

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Thangavelu, S., and C. Shunmuga Velayutham. "Taguchi Method Based Parametric Study of Generalized Generation Gap Genetic Algorithm Model." In Swarm, Evolutionary, and Memetic Computing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17563-3_42.

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Anagun, A. Sermet, and Feristah Ozcelik. "Optimization of Genetic Algorithm Parameters for Multi-channel Manufacturing Systems by Taguchi Method." In AI 2005: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11589990_133.

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Anand, K., S. Pratheesh Kumar, and S. Hari Chealvan. "Investigation on Machinability of EN8 Steel Through Taguchi Method, ANOVA and Genetic Algorithm." In Materials, Design and Manufacturing for Sustainable Environment. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3053-9_15.

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Samantra, Chitrasen, Kanchan Kumari, Abhishek Barua, Swastik Pradhan, and Prasant Ranjan Dhal. "Parametric Appraisal of Dry-Turning of EN24 using Taguchi-WASPAS and Sunflower Algorithm." In Sustainable Materials, Structures and IoT. CRC Press, 2024. http://dx.doi.org/10.1201/9781003596776-6.

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Conference papers on the topic "Taguchi's algorithm"

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Khedher, Ramzi, Jaouhar Fattahi, Ridha Ghayoula, et al. "Towards Reliable and Optimized IoT Applications Using Taguchi Algorithm and Intelligence." In 2024 17th International Congress on Advanced Applied Informatics (IIAI-AAI-Winter). IEEE, 2024. https://doi.org/10.1109/iiai-aai-winter65925.2024.00042.

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Zhu, Yan, Jianhua Xiang, and Zhengxing Zuo. "Research on the Cooling Water Chamber Structure of OP2S Engine Based on Taguchi Algorithm-Signal to Noise Ratio Analysis." In 2024 International Seminar on Artificial Intelligence, Computer Technology and Control Engineering (ACTCE). IEEE, 2024. https://doi.org/10.1109/actce65085.2024.00043.

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Chowdhury, Mazharul, Mohammad Islam, Abraham Gebregergis, and Tomy Sebastian. "Robust design optimization of permanent magnet synchronous machine utilizing genetic and Taguchi's algorithm." In 2013 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2013. http://dx.doi.org/10.1109/ecce.2013.6647376.

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Marlan, Zulkifli Marlah, Khairur Rijal Jamaludin, and Nolia Harudin. "Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method." In 2023 IEEE 11th Conference on Systems, Process & Control (ICSPC). IEEE, 2023. http://dx.doi.org/10.1109/icspc59664.2023.10420191.

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Tsai, S. C., and K. M. Ragsdell. "Orthogonal Arrays and Conjugate Directions for Taguchi-Class Optimization." In ASME 1988 Design Technology Conferences. American Society of Mechanical Engineers, 1988. http://dx.doi.org/10.1115/detc1988-0035.

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Abstract The work of Genichi Taguchi has recently become a subject of great interest and promise amongst U.S. manufacturing companies. Dr. Taguchi’s philosophy contains two important elements [1] : 1. Quality loss is defined as deviation from target. 2. Quality can only be achieved economically by being designed in. Dr. Taguchi’s approach employs orthogonal arrays and analysis of variance (ANOVA) tables in place of Taylor-expansion methods[2]. This approach appears to provide an opportunity for greater accuracy and proven convenience for practical engineering problems. This paper reports on a

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Yu, Jyh-Cheng, Tsung-Ren Hung, and Francis Thibault. "Performance Optimization of Extrusion Blow Molded Parts Using Fuzzy Neural-Taguchi Method and Genetic Algorithm." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/dac-34047.

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This paper presents a soft computing strategy to determine the optimal die gap parison programming of extrusion blow molding process. The design objective is to minimize part weight subject to stress constraints. The finite-element software, BlowSim, is used to simulate the parison extrusion and the blow molding processes. However, the simulations are time consuming, and minimizing the number of simulation becomes an important issue. The proposed strategy, Fuzzy Neural-Taguchi and Genetic Algorithm (FUNTGA), first establishes a back propagation network using Taguchi’s experimental array to pre

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Kim, HyungTae, SeungTaek Kim, KyungChan Jin, Jongseok Kim, and SungHo Lee. "Robust Parameter Design of Derivative Optimization Methods for Image Acquisition Using a Color Mixer." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50568.

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A tuning method was proposed for automatic lighting (auto-lighting) algorithms derived from the steepest descent and conjugate gradient methods. The auto-lighting algorithms maximize the image quality of the industrial machine vision by adjusting multiple-color light emitting diodes (LEDs), usually called color mixers. Searching for the driving condition for achieving maximum sharpness, which influences image quality, using multiple color LEDs, is time-consuming. Hence, the steepest descent and conjugate gradient methods were applied to reduce the searching time for achieving maximum image qua

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Yang, Cheng-Hong, Yu-Da Lin, and Li-Yeh Chuang. "Taguchi-enhanced binary differential evolution algorithm." In 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2017. http://dx.doi.org/10.1109/uic-atc.2017.8397654.

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Yigit, Mahmud Esad, and Tayfun Gunel. "Conformal antenna array synthesis using Taguchi Algorithm." In 2013 8th International Conference on Electrical and Electronics Engineering (ELECO). IEEE, 2013. http://dx.doi.org/10.1109/eleco.2013.6713882.

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Yaltirik, Hu¨seyin, A. Kerim Kar, and Bu¨lent Ekici. "Comparison of Contact Force Control Strategies on Different Robot Arm Types." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25404.

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Nowadays robots are used in various areas. There are extremely important applications where the robot arm tip comes in contact with the environment or an object. During controlling an object, static or in motion, the object or the robot arm should not be damaged. The interaction forces are important in such conditions. Whether the task succeeds or fails depends on how accurate the interaction forces are controlled. The interaction forces are changed depending on the motion of the robot arm. Therefore, to control interaction forces a force control algorithm must be developed. In this research a

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