Search Results - (( evolution optimization svm algorithm ) OR ( variable equalization based algorithm ))
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Classification for large number of variables with two imbalanced groups
Published 2020“…Based on the findings, Algorithm 2 outperforms Algorithm 1 in classifying the minority group, while both proposed algorithms perform equally well in classifying the majority group. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…ORPD problem is a nonlinear optimization problem that involving both equality constraints and inequality constraints. The proposed algorithms are tested on five different case studies which are IEEE 30-bus system with 13 control variables, IEEE 30-bus system with 19 control variables, IEEE 30-bus system with 25 control variables, IEEE 57-bus system with 25 control variables and IEEE 118-bus system with 77 control variables. …”
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Message based random variable length key encryption algorithm.
Published 2009“…In order to overcome analysis mentioned above a new algorithm is designed that is based on random numbers and also can defeat time and memory constraints. …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems
Published 2015“…The complicated task of design optimization of compact heat exchangers (CHEs) have been effectively performed by using evolutionary algorithms (EAs) in the recent years. However, mainly due to difficulties of handling extra variables, the design approach has been based on constant rates of heat duty in the available literature. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Development of committee machine models for multiple response optimization problems
Published 2014“…The results represent Global Desirability of proposed algorithm is equal or higher than GD of case studies. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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A novel quantum calculus-based complex least mean square algorithm (q-CLMS)
Published 2022“…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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A novel quantum calculus-based complex least mean square algorithm (q-CLMS)
Published 2022“…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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A novel quantum calculus-based complex least mean square algorithm (q-CLMS)
Published 2023“…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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A heuristic approach for finding similarity indexes of multivariate data sets
Published 2020“…Experiments were conducted with both benchmark and real time MDSs for evaluating the proposed algorithm`s performance against its rival algorithms, which are traditional dynamic programming based and sequential similarity measure algorithms. …”
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DESIGN AND DEVELOPMENT OF HIGH-ACCURACY MACHINE FOR WIRE BENDING
Published 2023“…Ten different dimensions of an equilateral triangle design sample with ten tries for each dimension (variable flange length, fixed bending angle equals to 60 degrees and bending radius equals to 3 mm) have been selected being produced using the bending machine, and the products have been formed two times. …”
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…In this thesis, a new quaternion gradient based adaptive algorithm for FIR adaptive filter is developed. …”
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