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Function estimation using a neural-fuzzy network and an improved genetic algorithm

H.K. Lam, S.H. Ling, F.H.F. Leung, P.K.S. Tam
2004 International Journal of Approximate Reasoning  
A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network.  ...  This paper presents the estimation of the transmission gains for an AC power line data network in an intelligent home. The estimated gains ensure the transmission reliability and efficiency.  ...  Acknowledgements The work described in this paper was substantially supported by a Research Grant of the Centre for Multimedia Signal Processing, The Hong Kong Polytechnic University (project number A432  ... 
doi:10.1016/j.ijar.2003.10.008 fatcat:a5mstwd2l5ctjlc3a3ry25vtsu

Genetic optimization of neural network and fuzzy logic for oil bubble point pressure modeling

Mohammad Afshar, Amin Gholami, Mojtaba Asoodeh
2014 Korean Journal of Chemical Engineering  
The present study went further by optimizing fuzzy logic and neural network models using the genetic algorithm in charge of eliminating the risk of being exposed to local minima.  ...  This strategy is capable of significantly improving the accuracy of both neural network and fuzzy logic models. The proposed methodology was successfully applied to a dataset of 153 PVT data points.  ...  CASE STUDY Neural Network Model and Genetic Optimized Neural Network A three-layered neural network with back-propagation algorithm was used for construction of an intelligent model which is meant  ... 
doi:10.1007/s11814-013-0248-8 fatcat:ztinxjkvrzhpha7bdkeady4dfi

Soft computing techniques for software effort estimation [article]

Sumeet Kaur Sehra, Yadwinder Singh Brar, Navdeep Kaur
2013 arXiv   pre-print
Soft computing is a consortium of methodologies centering in fuzzy logic, artificial neural networks, and evolutionary computation.  ...  These methodologies are currently used for reliable and accurate estimate of software development effort, which has always been a challenge for both the software industry and academia.  ...  An effort based model is proposed by [4] for estimation of COCOMO model using genetic algorithm. The algorithm considers methodology linearly related to effort.  ... 
arXiv:1310.5221v1 fatcat:67m6zixa4rhidmu6doqmigpysy

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

Mojtaba Asoodeh, Parisa Bagheripour, Amin Gholami
2015 Acta Geophysica  
Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative  ...  condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models.  ...  Therefore, the use of hybrid genetic algorithm-pattern search tool instead of back-propagation algorithm in the structure of neural network will improve the accuracy of modeling and eliminate the probability  ... 
doi:10.1515/acgeo-2015-0003 fatcat:lcl4odrdvnbtrnppyuvaklaeku

Genetic neuro-fuzzy architectures for advanced intelligent systems [chapter]

Sung-Bae Cho
1996 Advanced IT Tools  
As a manifestation, we propose an efficient fuzzy neural system which consists of modular neural networks combined by the fuzzy integral in which genetic algorithm determines the fuzzy density values.  ...  This paper presents a framework for developing intelligent systems based on several softcomputing techniques such as fuzzy logic, neural networks and genetic algorithm.  ...  On the other hand, genetic algorithm is a powerful tool for structure optimization of the fuzzy logic and the neural networks which provide an evaluation functions for the genetic algorithm.  ... 
doi:10.1007/978-0-387-34979-4_40 fatcat:fhu23ii3r5d5fdvczax7rtunxy

Artificial Intelligence Techniques in Solar Energy Applications [chapter]

Soteris Kalogirou, Arzu Senc
2010 Solar Collectors and Panels, Theory and Applications  
Solar Collectors and Panels, Theory and Applications 316 estimation of solar radiation, solar heating, photovoltaic (PV) systems, sun tracking systems, solar air-conditioning systems and many others.  ...  Esen et al. (2009) proposed the modelling of a solar air heater system by using an artificial neural network and wavelet neural network.  ...  of an isolated island-Sandwip in Bangladesh using genetic algorithms.  ... 
doi:10.5772/10343 fatcat:5zepz6ek2bfg3l57harzkxx3au

Microcomputer applications of hybrid intelligent systems

Larry R. Medsker
1996 Journal of Network and Computer Applications  
The integration of neural networks and expert systems has proven to be a useful way to develop real-world applications, and other intelligent technologies including fuzzy logic, genetic algorithms, and  ...  This article presents an analysis of the strengths and limitations of these five intelligent technologies, models for hybrid systems, and a review of the status and significance of research on and development  ...  Organization of the NeuroGENESYS method for optimizing neural networks with genetic algorithms. advantages of genetic algorithms to improve the design and use of neural networks [46] [47] [48] .  ... 
doi:10.1006/jnca.1996.0015 fatcat:jctv4s7chvbj7jteqbgwittxfu

Software Reliability Modeling using Soft Computing Techniques: Critical Review

Kaswan KS Choudhary S
2015 Journal of Information Technology & Software Engineering  
Then some technique is also used in the combination with the others as Neuro-Fuzzy, the combination of Neural Network and Fuzzy Logic.  ...  Neural Networks According to Nigrin A neural network is a circuit composed of a very large number of simple processing elements that are neurally based.  ...  perceptron neural network, radial-basis functions, Elman recurrent neural networks and a neuro-fuzzy model, for modeling the software reliability prediction.  ... 
doi:10.4172/2165-7866.1000144 fatcat:mar6yvi7ejenzhwa3bgmwkxheq

Software Reliability Modeling using Soft Computing Techniques: Critical Review

Kuldeep Singh Kaswan, Sunita Choudhary, Kapil Sharma
2015 International Journal of Information Technology and Computer Science  
and can be used globally.  ...  In this paper, we have provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability.  ...  perceptron neural network, radial-basis functions, Elman recurrent neural networks and a neuro-fuzzy model, for modeling the software reliability prediction In [29] [30] Singh et al. used feed forward  ... 
doi:10.5815/ijitcs.2015.07.10 fatcat:ab7t7unlcnhmtm6vad3ymvtlvy

An Evolutionary Functional Link Neural Fuzzy Model for Financial Time Series Forecasting

S. Chakravarty, P. K. Dash, V. Ravikumar Pandi, B. K. Panigrahi
2011 International Journal of Applied Evolutionary Computation  
Fu-yuan (2008b) has adopted a combination of improved PSO algorithm and fuzzy neural network to predict Shanghai stock market indices and genetic fuzzy neural network (Fu-yuan, 2008a) to forecast Shhenzhen  ...  A fuzzy neural network is used (Yu & Zhang, 2005) to forecast financial time series where genetic algorithm and gradient descent learning algorithm are used alternatively in an iterative manner to adjust  ... 
doi:10.4018/jaec.2011070104 fatcat:y6ykaolnrzelxcywasw7axjn4a

Analysis of Sports Injury Estimation Model Based on Mutation Fuzzy Neural Network

Dong Wang, Jeng-Sheng Yang, Syed Hassan Ahmed
2021 Computational Intelligence and Neuroscience  
of mutation fuzzy neural network.  ...  In order to improve the calculation efficiency of sports injury estimation results and save the cost of estimation and analysis, we propose a sports injury estimation model based on the algorithm model  ...  In this study, the genetic algorithm is used to optimize the fuzzy neural network, and on this basis, the membership function parameters and rule weight values are optimized, so as to obtain a simplified  ... 
doi:10.1155/2021/3056428 pmid:34899890 pmcid:PMC8654572 fatcat:tzdbq5zi75fqlpopeu2zsvto7u

Software development effort estimation modeling using a combination of fuzzy-neural network and differential evolution algorithm

Amir Karimi, Taghi Javdani Gandomani
2021 International Journal of Power Electronics and Drive Systems (IJPEDS)  
This study presents a new model based on a hybrid of adaptive network-based fuzzy inference system (ANFIS) and differential evolution (DE) algorithm.  ...  could improve the accuracy using MMRE and PRED (0.25) criteria up to 7%.  ...  ., [24] used the hybrid PSO algorithm and fuzzy neural network model to improve results. They used NASA datasets.  ... 
doi:10.11591/ijece.v11i1.pp707-715 fatcat:x7dfvbxn7fgrvgxj5h4toqcnji

On-line genetic algorithm-based fuzzy-neural sliding mode controller using improved adaptive bound reduced-form genetic algorithm

Ping-Zong Lin, Wei-Yen Wang, Tsu-Tian Lee, Chi-Hsu Wang
2009 International Journal of Systems Science  
To identify structured system dynamics, a B-spline membership function fuzzy-neural network, which is trained by the improved genetic algorithm, is used to approximate the regressor of the robot manipulator  ...  2009) On-line genetic algorithm-based fuzzy-neural sliding mode controller using improved adaptive bound reduced-form genetic algorithmIn this article, a novel on-line genetic algorithm-based fuzzy-neural  ...  For the purpose of using W and ' to approximate Y*, we use a B-spline membership function fuzzy-neural network as an approximator, and an improved adaptive bound reduced-form genetic algorithm to adjust  ... 
doi:10.1080/00207720902750011 fatcat:ab2egqel2zanzezn6qhizbjcwe

High-performance adaptive intelligent Direct Torque Control schemes for induction motor drives

M. Vasudevan, R. Arumugam, S. Paramasivam
2005 Serbian Journal of Electrical Engineering  
In this paper, the performance of the various sensorless intelligent Direct Torque Control (DTC) techniques of Induction motor such as neural network, fuzzy and genetic algorithm based torque controllers  ...  controllers are used.  ...  DTC USING GENETIC ALGORITHM Neural network trained with genetic algorithm is implemented in such a way that the total number of thresholds and weights of the neural network be packed in n -dimensional  ... 
doi:10.2298/sjee0501093v fatcat:he6i4dtierdj7jbkqqa2fhhptu

Location Finding in Wireless Sensor Network Based on Soft Computing Methods

Seyed Mohammad Nekooei, M. T. Manzuri-Shalmani
2011 2011 International Conference on Control, Automation and Systems Engineering (CASE)  
In this work, genetic fuzzy and neuro -fuzzy methods are used to become more accurate localization.  ...  Sensor Localization is a crucial part of many location dependent applications that is utilized in wireless sensor networks (WSNs).  ...  Fuzzy membership functions of RSSI To achieve more precise weight for WCL, we have trained the fuzzy logic system with genetic algorithms and neural networks.  ... 
doi:10.1109/iccase.2011.5997582 fatcat:cekk3ummnzatzok6koxag5pz6y
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