Search Results - (( evolution evaluation method algorithm ) OR ( variable selection process algorithm ))

Shear strength test on unsaturated soil using natural microscopic surface tension force / Basharudin Abdul Hadi by Abdul Hadi, Basharudin

“…The research aims to evaluate the performance and hydrological response of the Soil Water Assessment Tool (SWAT) process-based model in tropical river basin using Malaysia soil data. …”
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Multi-criteria optimization framework for cloudlet computing in WMANs: integrating VL-WIDE and AHP for enhanced decision-making by Muwafaq, Layth, Noordin, Nor K, Othman, Mohamed, Ismail, Alyani, Hashim, Fazirulhisyam

“…Comprehensive time-series evaluations demonstrate that our framework significantly outperforms conventional systems and other benchmark algorithms, with VL-WIDE and AHP achieving the lowest root mean square error (RMSE) of 16.7, a 5.1% improvement over random selection. …”
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SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid by Khalid, Khairi

“…The research aims to evaluate the performance and hydrological response of the Soil Water Assessment Tool (SWAT) process-based model in tropical river basin using Malaysia soil data. …”
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SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid by Khalid, Khairi

“…The research aims to evaluate the performance and hydrological response of the Soil Water Assessment Tool (SWAT) process-based model in tropical river basin using Malaysia soil data. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Kohbalan, Moorthy, Shahreen, Kasim, Ashraf Osman, Ibrahim

“…This paper present a hybrid method of Newton method, Differential Evolution Algorithm (DE) and Cooperative Coevolution Algorithm (CCA). …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

“…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…An experimental study was conducted, and the variable selection process using the normalization-based Binary Bat algorithm found a better combination of input variables which consists of only six out of eight variables. …”

SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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New selection algorithm for Mengubah Destini Anak Bangsa (MDAB) students / Zamali Tarmudi ... [et al.] by Tarmudi, Zamali, Saibin, Tammie Christy, Naharu, Nasrah, Ung, Ling Ling

“…It focuses on the refinement and modification of certain variables in selection process. The technique employs the intersection of fuzzy goals and constraints concept in judgmental process. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…Model structure selection is one of the important steps in a system identification process. …”
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Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents the integration of Mixed Variable Ant Colony Optimization and Support Vector Machine (SVM) to enhance the performance of SVM through simultaneously tuning its parameters and selecting a small number of features.The process of selecting a suitable feature subset and optimizing SVM parameters must occur simultaneously,because these processes affect each ot her which in turn will affect the SVM performance.Thus producing unacceptable classification accuracy.Five datasets from UCI were used to evaluate the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with the small size of features subset.…”
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Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Safaai, Deris, Mohd Saberi, Mohamad, Shahreen, Kasim, Saedudin, Rd Rohmat

“…Due to that, this study proposed and improved a method that comprises with Newton method, differential evolution algorithm (DE) and competitive co-evolutionary algorithm(ComCA). …”
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LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

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Channel-aware downlink scheduling for quality of service in long term evolution network by Najim, Alaa Omer

“…The proposed algorithm using system-level simulation experiments with performance comparison with DBWPF in terms of end-to-end delay, fairness, system throughput, Packet Loss Ratio (PLR), and spectral efficiency was evaluated. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

“…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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