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Journal articles on the topic 'SOFT COMPUTING TECHNIQUE'

Author: Grafiati

Published: 11 September 2023

Last updated: 25 July 2025

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1

Sabri, Norlina M., Mazidah Puteh, and Mohamad Rusop Mahmood. "Utilization of Soft Computing Techniques in Sputtering Processes: A Review." Advanced Materials Research 832 (November 2013): 260–65. http://dx.doi.org/10.4028/www.scientific.net/amr.832.260.

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This paper presents an overview of research works on the utilizing of soft computing in the optimization of process parameters and in the prediction of thin film properties in sputtering processes. The papers from this review were obtained from relevant databases and from various scientific journals. The papers collected were published from 2008 to 2012. The focus of the review is to provide an outlook on the utilization of soft computing techniques in sputtering processes. Based on the review, the soft computing techniques which have been applied so far are ANN, GA and Fuzzy Logic. The first

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Yu, Yingbing. "Anomaly Intrusion Detection Based upon Anomalous Events and Soft Computing Technique." International Journal of Machine Learning and Computing 5, no. 6 (2015): 450–53. http://dx.doi.org/10.18178/ijmlc.2015.5.6.550.

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Hasan, Basri KARTAL, and Nisa KARTAL Asiye. "Some Examples on the 'Evolutionary &Genetic', and 'Artificial Life' Strategies in Architectural Design." International Journal of Arts and Social Science 4, no. 2 (2023): 223–31. https://doi.org/10.5281/zenodo.7740258.

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Branches of soft computing emerged before the 1990s, but soft computing became an independent new discipline after the 1990s. Since then, soft computing became one of the top research areas in AI studies. Unlike other computing techniques, soft computing strategies are more tolerant to imprecision, uncertainty, probabilities, predictions, approximations. This technique has started to be used widely in a wide range of disciplines because it can quickly deal with solution sets, optimisation of solutions. Soft computing strategies generally take the human mind as a role model in architectural des

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Wong, K. W., P. M. Wong, T. D. Gedeon, and C. C. Fung. "Rainfall prediction model using soft computing technique." Soft Computing - A Fusion of Foundations, Methodologies and Applications 7, no. 6 (2003): 434–38. http://dx.doi.org/10.1007/s00500-002-0232-4.

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Kaur, Supreet, and Rajiv Mahajan. "Energy efficient clustering protocol for wireless sensor networks." Modern Physics Letters B 32, no. 32 (2018): 1850400. http://dx.doi.org/10.1142/s0217984918504006.

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In this paper, a hybrid soft computing technique-based energy efficient protocol is proposed to improve the inter-cluster data aggregation in clustering based general self-organized tree based energy balance (GSTEB) routing protocol. Initially, improved ant colony optimization-based technique is used to select optimal cluster heads. Afterwards, a hybrid soft computing technique is utilized to communicate the data from cluster heads to sink. Extensive experiments have been done by considering the existing and proposed technique. Experimental results indicate that the proposed technique provides

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Singh, Dharmpal. "An Effort to Design an Integrated System to Extract Information Under the Domain of Metaheuristics." International Journal of Applied Evolutionary Computation 8, no. 3 (2017): 13–52. http://dx.doi.org/10.4018/ijaec.2017070102.

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The main objective of this work is to develop an integrated system that is capable of extracting precise information (knowledge) based on any stored information using the techniques of data mining and soft computing. For the purpose of extracting precise information based on some stored information, it has been further observed that the research work related to the area of knowledge discovery based on certain information with the help of a particular data mining or soft computing model has been done, but the performance based on the particular soft computing or data mining model has not been r

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Shen, Zhongjie, Ahmed Farouk Deifalla, Paweł Kamiński, and Artur Dyczko. "Compressive Strength Evaluation of Ultra-High-Strength Concrete by Machine Learning." Materials 15, no. 10 (2022): 3523. http://dx.doi.org/10.3390/ma15103523.

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In civil engineering, ultra-high-strength concrete (UHSC) is a useful and efficient building material. To save money and time in the construction sector, soft computing approaches have been used to estimate concrete properties. As a result, the current work used sophisticated soft computing techniques to estimate the compressive strength of UHSC. In this study, XGBoost, AdaBoost, and Bagging were the employed soft computing techniques. The variables taken into account included cement content, fly ash, silica fume and silicate content, sand and water content, superplasticizer content, steel fib

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A., Dr Sathesh. "ENHANCED SOFT COMPUTING APPROACHES FOR INTRUSION DETECTION SCHEMES IN SOCIAL MEDIA NETWORKS." Journal of Soft Computing Paradigm 2019, no. 2 (2019): 69–79. http://dx.doi.org/10.36548/jscp.2019.2.002.

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The soft computing methods play a vital role in identifying the malicious activities in the social network. The low cost solutions and the robustness provided by the soft computing in the identifying the unwanted activities make it a predominant area of research. The paper combines the soft computing techniques and frames an enhanced soft computing approach to detect the intrusion that cause security issues in the social network. The proffered method of the paper employs the enhanced soft computing technique that combines the fuzzy logic, decision tree, K means -EM and the machine learning in

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Sindhwani, Manoj, Shippu Sachdeva, Krishan Arora, et al. "Soft Computing Techniques Aware Clustering-Based Routing Protocols in Vehicular Ad Hoc Networks: A Review." Applied Sciences 12, no. 15 (2022): 7922. http://dx.doi.org/10.3390/app12157922.

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The vehicular ad hoc network is an emerging area of technology that provides intelligent transportation systems with vast advantages and applications. Frequent disconnections between the vehicular nodes due to high-velocity vehicles impact network performance. This can be addressed by efficient clustering techniques. Several recent studies have attempted to develop optimal clustering algorithms to improve network performance metrics using soft computing techniques. Although sufficient work on soft computing techniques has been carried out, it seems less commonplace to find an analysis of vario

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Ifebanjo, Temitope M* Ogunleye Olawole M. Abiodun Theresa Nkechi Adebiyi Ayodele A. "SOFT COMPUTING APROACHES TO STOCK FORECASTING: A SURVEY." Global Journal of Engineering Science and Research Management 4, no. 5 (2017): 107–31. https://doi.org/10.5281/zenodo.801251.

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Soft computing techniques has been effectively applied in business, engineering, medical domain to solve problems in the past decade. However, this paper focuses on censoring the application of soft computing techniques for stock market prediction in the last decade (2010 - todate). Over a hundred published articles on stock price prediction were reviewed. The survey is done by grouping these published articles into: the stock market surveyed, input variable choices, summary of modelling technique applied, comparative studies, and summary of performance measures. This survey aptly shows that s

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S. Kumar Chandar, Dr. "Soft computing and bioinspired computing techniques for stock market prediction-a comprehensive survey." International Journal of Engineering & Technology 7, no. 3 (2018): 1836. http://dx.doi.org/10.14419/ijet.v7i3.14716.

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Stock Market Prediction (SMP) is one of the most important and hottest topics in business and finance. The main goal of SMP is to develop an efficient technique to predict stock values and achieves accurate results with minimum number of input data. This research paper reviews currently available SMP techniques based on soft computing and bio inspired computing algorithms. Many issues in-volved in the SMP are identified and different techniques are studied along with their merits and demerits to find the most suitable one. This paper also analyses the performance of various techniques with res

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KumarSaini, Dinesh, and Jabar H Yousif. "Environmental Scrutinizing System based on Soft Computing Technique." International Journal of Computer Applications 62, no. 13 (2013): 45–50. http://dx.doi.org/10.5120/10143-4952.

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Manh, Linh Ho, Francesco Grimaccia, Marco Mussetta, and Riccardo E. Zich. "A Soft Computing Hybridization Technique for Antenna Optimization." International Journal on Communications Antenna and Propagation (IRECAP) 5, no. 1 (2015): 16. http://dx.doi.org/10.15866/irecap.v5i1.4899.

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Sudipta Sen, Sudipta Sen. "Hydro-Thermal Scheduling: Using Soft Computing Technique Approch." IOSR Journal of Electrical and Electronics Engineering 5, no. 6 (2013): 55–80. http://dx.doi.org/10.9790/1676-0565580.

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Ghadiyali, Tejaskumar, and Kalpesh Lad. "Risk Minimization in Agribusiness using Soft Computing Technique." IOSR Journal of Computer Engineering 18, no. 05 (2016): 20–25. http://dx.doi.org/10.9790/0661-1805042025.

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Sesadri, U., B. Siva Sankar, and C. Nagaraju. "Type2 Fuzzy Soft Computing Technique for Image Enhancement." IAES International Journal of Artificial Intelligence (IJ-AI) 4, no. 3 (2015): 97. http://dx.doi.org/10.11591/ijai.v4.i3.pp97-104.

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<p class="Default">The mainpurpose of Image enhancement is to process an image so that outcome is more appropriate than original image for definite application. The fuzzy logic isone of the soft computing techniques to enhance the images by eliminating uncertainty.In this paper efficient type2 fuzzy logic technique is used to get betterquality image. This method consists of two steps. In the First step fisher criterion function is useful to generate type1 fuzzy membership value. In the second step based on type1 membership value fuzzy rules are derived to enhance the image. The type2 fuz

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Das, Ratnakar, Jibitesh Mishra, Pradyumna Kumar Pattnaik, and Muhammad Mubashir Bhatti. "Prediction of Heatwave Using Advanced Soft Computing Technique." Information 14, no. 8 (2023): 447. http://dx.doi.org/10.3390/info14080447.

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At present, there is no suitable instrument available to simulate modeling the thermal performance of various areas of our states due to its complicated meteorological behavior. To accurately predict a heatwave, we studied the research gaps and current ongoing research on the prediction of heatwaves. For the accurate prediction of a heatwave, we considered two soft computing concepts, (a) Rough Set Theory (RST) and (b) Support Vector Machine (SVM). All the ongoing research on the prediction of heatwaves is based on future predictions with an error margin. All the available techniques use a par

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Yadav, Yogesh, and Ishwor Singh Saud. "Development of a Model Updating Technique Using Soft Computing." Journal of Advanced College of Engineering and Management 7, no. 01 (2022): 183–90. http://dx.doi.org/10.3126/jacem.v7i01.47344.

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The structural models, do not necessarily predict the measured data sufficiently accurately. Because of this, there is a need for these models to be updated to better reflect the measured data. This paper introduces computational intelligence techniques to update finite element models. The model updating is formulated as a constrained optimization problem and solved using a recently developed meta-heuristic algorithm called Artificial Bee Colony (ABC) algorithm. A MATLAB code is developed using the model-updating formulations presented in this paper. Numerical simulation studies are carried ou

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LV, Yingli, Qui-Thao Le, Hoang-Bac Bui, et al. "A Comparative Study of Different Machine Learning Algorithms in Predicting the Content of Ilmenite in Titanium Placer." Applied Sciences 10, no. 2 (2020): 635. http://dx.doi.org/10.3390/app10020635.

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In this study, the ilmenite content in beach placer sand was estimated using seven soft computing techniques, namely random forest (RF), artificial neural network (ANN), k-nearest neighbors (kNN), cubist, support vector machine (SVM), stochastic gradient boosting (SGB), and classification and regression tree (CART). The 405 beach placer borehole samples were collected from Southern Suoi Nhum deposit, Binh Thuan province, Vietnam, to test the feasibility of these soft computing techniques in estimating ilmenite content. Heavy mineral analysis indicated that valuable minerals in the placer sand

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Issa, Abbas H., and Ali H. Majeed. "Intelligent sensor fault detection based on soft computing." Kufa Journal of Engineering 4, no. 1 (2014): 113–24. http://dx.doi.org/10.30572/2018/kje/411246.

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Sensor fault detection is carried out based on the characteristics of the soft computing techniques; neural network and adaptive neural fuzzy inference system ANFIS. In this paper, a neural network (non-model based technique) and ANFIS has been used for detection and isolation of temperature sensor fault TMP36. The measured states are then compared with true estimated states and if their difference exceeds threshold value, the particular sensor measurement is ignored and replaced by the true estimated state. Residual generation is an essential part of model-based fault detection schemes. This

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21

Mathur, Ashwani. "Image Retrieval by Soft Computing Technique and Visual Features." International Journal of Computer Applications 174, no. 16 (2021): 8–12. http://dx.doi.org/10.5120/ijca2021921047.

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22

Vijayeeta, Prachi, Utsav Kar, Madhurima Rana, Madhabananda Das, and B. S. P. Mishra. "Microarray Classification of Cancerous Cell Using Soft Computing Technique." Procedia Computer Science 49 (2015): 66–73. http://dx.doi.org/10.1016/j.procs.2015.04.228.

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Vyas, Vidhi, Ajit Pratap Singh, and Anshuman Srivastava. "Quantification of airfield pavement condition using soft-computing technique." World Journal of Engineering 17, no. 6 (2020): 877–90. http://dx.doi.org/10.1108/wje-01-2020-0021.

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Purpose The purpose of this study is the development of an objective approach to prioritize and rank airfield pavement sections based on their condition and justify their funding requirements using a soft-computing technique. Design/methodology/approach The airfield pavement condition is evaluated by collecting data through field tests and visual surveys. The performance indicators are selected as deflection, structural index, subgrade modulus and pavement condition index, by taking the help of field experts. The condition of pavement sections is analyzed by obtaining scores for each sections

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Deshpande, Ms Pooja S., and Prof S. J. Honade. "Brain Tumor Segmentation and Detection using Soft Computing Technique." IOSR Journal of Electronics and Communication Engineering 12, no. 02 (2017): 129–44. http://dx.doi.org/10.9790/2834-120203129144.

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Chanda, Mriganka Mohan, Neelotpaul Banerjee, and Gautam Bandyopadhyay. "Effective Implementation of Knowledge Management Systems (KMS) in Government Schemes/Programs of Selected Sectors Using Soft Computing." International Journal of Knowledge Management 18, no. 1 (2022): 1–22. http://dx.doi.org/10.4018/ijkm.297608.

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Soft Computing (SC) technique consisting of several fields of Artificial Intelligence namely, Artificial Neural Networks (ANNs), Fuzzy Logic (FL), Genetic Algorithms (GA), Machine Learning (ML) and Probabilistic Reasoning (PR) is a new paradigm in computing based on a creative mix of comparatively newer computing techniques. Here, we have taken into consideration several important schemes/ programs of selected sectors pertaining to different Central Ministries/ Departments of Government of India and observed that proper Knowledge Management System (KMS) can be developed and implemented in such

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Sitinoor, Adeib Idris, and Markom Masturah. "Overview of soft intelligent computing technique for supercritical fluid extraction." International Journal of Advances in Applied Sciences (IJAAS) 9, no. 2 (2020): 117–24. https://doi.org/10.11591/ijaas.v9.i2.pp117-124.

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Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the process behavi

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Prashanth, R., and D. S. Nimaje. "Estimation of peak particle velocity using soft computing technique approaches: a review." Noise & Vibration Worldwide 49, no. 9-10 (2018): 302–10. http://dx.doi.org/10.1177/0957456518799536.

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Ground vibrations caused by blasting are undesirable consequences in the mining industry. It can cause serious damage to the nearby buildings and facilities. Hence, such vibrations have to be controlled to reduce the damage to the environment, and this may be achieved by predicting the blast peak particle velocity. The induced peak particle velocity has influenced by a number of parameters. They are spacing, burden, distance from the blast site, maximum explosive charge per delay, number of holes, stemming, and hole diameter. Existed empirical predictor approaches were used to evaluate the gro

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Tanaka, Kazuo. "Advanced Computational Intelligence in Control Theory and Applications." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 2 (1999): 67. http://dx.doi.org/10.20965/jaciii.1999.p0067.

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We are witnessing a rapidly growing interest in the field of advanced computational intelligence, a "soft computing" technique. As Prof. Zadeh has stated, soft computing integrates fuzzy logic, neural networks, evolutionary computation, and chaos. Soft computing is the most important technology available for designing intelligent systems and control. The difficulties of fuzzy logic involve acquiring knowledge from experts and finding knowledge for unknown tasks. This is related to design problems in constructing fuzzy rules. Neural networks and genetic algorithms are attracting attention for t

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Govind, Annu, Vijay Kumar Tayal, and Prakash Kumar. "Performance enhancement of shunt active power filter using soft computing techniques." International Journal of Applied Power Engineering (IJAPE) 10, no. 3 (2021): 253. http://dx.doi.org/10.11591/ijape.v10.i3.pp253-261.

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Nowadays, active power filter (APF) is the most popular device for harmonic compensation. This paper presents the soft computing techniques for compensation of currents harmonics using a shunt active power filter (SAPF). The method includes a 3-phase supply system with a current-controlled voltage source converter (CC-VSC) having an input coupling inductor and output tank capacitor for a self-supported DC bus. The performance of the active power filter can be enhanced by using soft computing techniques such as artificial neural network (ANN) controller and gravitational search algorithm (GSA)

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Annu, Govind, Kumar Tayal Vijay, and Kumar Prakash. "Performance enhancement of shunt active power filter using soft computing techniques." International Journal of Applied Power Engineering (IJAPE) 10, no. 3 (2021): 253–61. https://doi.org/10.11591/ijape.v10.i3.pp253-261.

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Nowadays, active power filter (APF) is the most popular device for harmonic compensation. This paper presents the soft computing techniques for compensation of currents harmonics using a shunt active power filter (SAPF). The method includes a 3-phase supply system with a currentcontrolled voltage source converter (CC-VSC) having an input coupling inductor and output tank capacitor for a self-supported DC bus. The performance of the active power filter can be enhanced by using soft computing techniques such as artificial neural network (ANN) controller and gravitational search algorithm (GSA) f

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Annu, Govind, Kumar Tayal Vijay, and Kumar Prakash. "Performance enhancement of shunt active power filter using soft computing techniques." International Journal of Applied Power Engineering 13, no. 3 (2021): 253~261. https://doi.org/10.5281/zenodo.7344521.

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Nowadays, active power filter (APF) is the most popular device for harmonic compensation. This paper presents the soft computing techniques for compensation of currents harmonics using a shunt active power filter (SAPF). The method includes a 3-phase supply system with a currentcontrolled voltage source converter (CC-VSC) having an input coupling inductor and output tank capacitor for a self-supported DC bus. The performance of the active power filter can be enhanced by using soft computing techniques such as artificial neural network (ANN) controller and gravitational search algorithm (GSA) f

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32

Nadaradjane, S. M. R., B. Priyenga, and N. Sanjay. "Clinical level diagnosis of chagas disease using soft computing technique." International Journal of Infectious Diseases 101 (December 2020): 433–34. http://dx.doi.org/10.1016/j.ijid.2020.09.1136.

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S.P.shukla, Mr, and Mrs Ritu Dwivedi. "Clustering and Classification of Cancer Data Using Soft Computing Technique." IOSR Journal of Computer Engineering 16, no. 1 (2014): 32–36. http://dx.doi.org/10.9790/0661-16113236.

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Abed, Wathiq, Qais Aish, and Ahmmed Hamed. "Performance monitoring of aircraft PMSM based on soft computing technique." Periodicals of Engineering and Natural Sciences (PEN) 9, no. 1 (2021): 293. http://dx.doi.org/10.21533/pen.v9i1.1797.

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Srujan kumar, Gudiboyana, Korra Mohan rao, and N. Praneeth. "A Simple and Efficient Soft Computing Technique for Optimizing Mechatronics." International Journal of Engineering Trends and Technology 22, no. 9 (2015): 443–46. http://dx.doi.org/10.14445/22315381/ijett-v22p290.

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Idris, Sitinoor Adeib, and Masturah Markom. "Overview of soft intelligent computing technique for supercritical fluid extraction." International Journal of Advances in Applied Sciences 9, no. 2 (2020): 117. http://dx.doi.org/10.11591/ijaas.v9.i2.pp117-124.

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<span>Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the pr

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Samira, Kalantari, Amiri besheli Mohsen, Sam Daliri Zeinab, Shamshirb Shahaboddin, and Shing Ng Liang. "Routing in wireless sensor network based on soft computing technique." Scientific Research and Essays 6, no. 21 (2011): 432–4441. http://dx.doi.org/10.5897/sre10.306.

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Das, Gourab. "Techno-economic analysis of novel multi-objective soft computing technique." International Journal of Bio-Inspired Computation 20, no. 3 (2022): 172. http://dx.doi.org/10.1504/ijbic.2022.10052581.

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Das, Gourab. "Techno-economic analysis of novel multi-objective soft computing technique." International Journal of Bio-Inspired Computation 20, no. 3 (2022): 172. http://dx.doi.org/10.1504/ijbic.2022.127505.

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Maddineni, Bhavyasri. "Analysis of Beam Forming Antenna using Soft-Computing Techniques." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 661–65. http://dx.doi.org/10.22214/ijraset.2021.35050.

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Antenna Beam forming is a technology or a technique that is finding increasing use in systems of cellular telecommunication, especially 5G, as well as many other wireless systems. Beam forming refers to the formation of a beam of energy from a set of phased arrays. With the use of phased arrays, it is possible to control the direction and shape of the beam from multiple antennas, based on the spacing between antennas and the phase of signal from each antenna element in the array. Beam forming focuses a wireless signal towards a specific receiving device, rather than having the signal spread in

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Nagesh, H., and R. S. Shivakumara Aradhya. "A Review on Application of Soft Computing Techniques for Load Shedding in Power Systems." Asian Journal of Electrical Sciences 7, no. 2 (2018): 61–64. http://dx.doi.org/10.51983/ajes-2018.7.2.2159.

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In power systems, system frequency decreases if load exceeds generation and increases when power generation is greater than load demand. Load shedding is highly required in power systems to stabilize frequency in electrical power systems. Though conventional load shedding techniques are being used in many power system applications, soft computing techniques such as artificial neural networks (ANNs), fuzzy logic, genetic algorithm and particle swarm optimization have been presented by many researchers to provide optimum load shedding. However, there are many problems associated with machine lea

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Ilango, S. Sudhakar, and V. Seenivasagam. "Wavelet Based Image Compression Using Soft Computing Techniques." Applied Mechanics and Materials 573 (June 2014): 477–82. http://dx.doi.org/10.4028/www.scientific.net/amm.573.477.

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The Wavelet Transform is a multi-resolution transform, that is, it allows a form of time–frequency analysis (or translation–scale in wavelet speak). When using the Fourier transform the result is a very precise analysis of the frequencies contained in the signal, but no information on when those frequencies occurred. The wavelet based image compression algorithms are used widely compared with other conventional compression algorithms. The wavelet coding based on the coefficient selection and sub band level. In this paper we have used two wavelets such as spherical and geometric wavelets. The s

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Crawford, Broderick, Ricardo Soto, Eric Monfroy, Carlos Castro, Wenceslao Palma, and Fernando Paredes. "A Hybrid Soft Computing Approach for Subset Problems." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/716069.

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Subset problems (set partitioning, packing, and covering) are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S) can be partitioned into smaller subsets. All items inSmust be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions) and set covering (all items must be contained in at least one partition). Here, we present a hybrid solver based on ant colony optimization (ACO) combined with arc consistency for solving this kind of problems. ACO is a swa

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Neshe, Nishat Nabila Haque, and Manwinder Singh. "Hybrid Spectrum Sensing Techniques in 5G Cognitive Radio Networks in Soft Computing: A Review." Computational Intelligence and Machine Learning 2, no. 1 (2021): 40–49. http://dx.doi.org/10.36647/ciml/02.01.a006.

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This paper describes an updated and efficient method for Hybrid spectrum sensing in cognitive radio (CR) system utilizing soft computing paradigms. The suggested soft computing approach utilizes an artificial neural network and for learning and decision making as a solution to the problems when a new product is subjected to the CR framework, developed the ability for unlicensed cognitive users to access radio frequencies through a spectrum hole and understand its implications through mechanisms spectrum sensing. The suggested soft computing approach could then be referred to as the Neuro techn

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Choudhury, Balamati, Sangeetha Manickam, and R. M. Jha. "Soft Computing Techniques for Mutual Coupling Reduction in Metamaterial Antenna Array." Journal of Optimization 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/252806.

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Application of soft computing techniques for various metamaterial designs and optimizations is an emerging field in the microwave regime. In this paper, a global optimization technique, namely, particle swarm optimization (PSO), is used for the design and optimization of a square split ring resonator (SSRR) having a resonant frequency of 2.4 GHz. The PSO optimizer yields the structural parameters, which is further simulated and validated with the optimized value. This optimized structure results in the mutual coupling reduction in a microstrip antenna array designed for wireless application.

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Rupinder Kaur, Vikas Kumar Garg and Shikha. "A Review on Various Soft Computing and Swarm Intelligence Techniques." International Journal for Modern Trends in Science and Technology 7, no. 07 (2022): 81–85. http://dx.doi.org/10.46501/ijmtst051237.

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This paper gives you the overview of the Soft computing techniques i.e. Genetic algorithm (GA), Artificial neural networks (ANN) and some of Swarm Intelligence techniques i.e. Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) etc. Soft Computing is basically an optimization technique which helps to find the results of problems which are very difficult to reply. It is the integration of methodologies which are planned to represent and find the solutions to real world problems that are not represented or which are very har

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Kumaraswamy, Durgam, and B. V. Sanker Ram. "Fuel Cell Power Conversion Enhancement using Fuzzy Based Soft Computing Technique." Indian Journal of Science and Technology 10, no. 23 (2017): 1–11. http://dx.doi.org/10.17485/ijst/2017/v10i23/101347.

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Zhang, Hong Min. "Path Planning Methods of Mobile Robot Based on Soft Computing Technique." Advanced Materials Research 216 (March 2011): 677–80. http://dx.doi.org/10.4028/www.scientific.net/amr.216.677.

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Path planning is one of the most important and challenging problems of mobile robot. It is one of the keys that will make the mobile robots fully autonomous. In this paper, we summarized the application of soft computing approaches in path planning for mobile robot. Finally the future works of path planning for mobile robots are prospected.

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Dhanasekar, N., and R. Kayalvizhi. "Soft Computing Technique for the Control of Triple-Lift Luo Converter." International Journal of Engineering Research and Applications 07, no. 03 (2017): 35–38. http://dx.doi.org/10.9790/9622-0703063538.

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Pallekonda, Ramesh Babu, Soumya Ranjan Nanda, Santosha K. Dwivedy, Vinayak Kulkarni, and Viren Menezes. "Soft Computing Based Force Recovery Technique for Hypersonic Shock Tunnel Tests." International Journal of Structural Stability and Dynamics 18, no. 05 (2018): 1871004. http://dx.doi.org/10.1142/s0219455418710049.

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A hemispherical model equipped with a three component accelerometer force balance has been tested in a shock tunnel at Mach 8.0 freestream conditions. A novel technique has been devised using the Artificial Neuro-Fuzzy Inference System (ANFIS) for recovering the forces experienced by the model during the experiments. Implementation of this methodology in calibration of the force balance showed encouraging agreement with the impulse forces recovered from the calibration tests. The same recovery procedure is then adopted to obtain the time history of the forces for 0[Formula: see text] and 15[Fo

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