Search Results - (( using optimization model algorithm ) OR ( evolution classification _ algorithm ))
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1
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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2
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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3
Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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4
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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5
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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6
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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7
Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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8
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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9
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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10
Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
11
Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. …”
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12
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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13
Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences
Published 2018“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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14
Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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15
Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization
Published 2018“…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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Research Report -
16
Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference
Published 2018“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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17
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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19
Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems
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Working Paper -
20
Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm
Published 2023“…This research aimed to establish a computational model that represents the ALB-EE, propose a new Tiki-Taka Algorithm (TTA) to solve and optimize the ALB-EE and validate the developed model through a real-life case study. …”
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