Search Results - (( variable optimization model algorithm ) OR ( java data visualization algorithm ))

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…This proposed algorithm also discerned linear and nonlinear subsystem variables within a continuous-time Hammerstein model utilizing input and output data. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

“…In preprocessing of optimization, modeFrontier Response Surface Method (RSM) is able to model the behavior of engine performances corresponding to the change of design variables.…”
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Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel by Hushairi, Zen, Al-Khalid, Hj Othman, Khairuddin, Abdul Hamid, Jamaah, Suut

“…A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. …”
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Variable Global Optimization min-sum (VGOMS) algorithm of decodeand-forward protocol for the relay node in the cooperative channel by Hushairi, Zen, Jamaah, Suut, Al-Khalid, Bin Hj Othman, Khairuddin, Bin Ab Hamid

“…A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. …”
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Development of genetic algorithm for optimization of yield models in oil palm production by Hilal, Yousif Y., Wan Ismail, Wan Ishak, Yahya, Azmi, Ash’aari, Zulfa Hanan

“…Moreover, models were built on the basis of variables that have been selected by the GA. …”
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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

“…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin by Nasaruddin, Amir Hambaly

“…The result of this project is all algorithm for visualizing data is functioning and the output produced from the system is correct and effective. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

“…Subsequently, the optimal parameters of the CatBoost algorithm are determined to streamline computational resource usage and reduce model complexity. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machine (SVM) is a present day classification approach originated from statistical approaches.Two main problems that influence the performance of SVM are selecting feature subset and SVM model selection. In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…4.457, and KGE = 0.737) compared to other models. Furthermore, the utilization of FA and ABC optimization techniques facilitated the optimization of the ANN model parameters. …”

Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…s orthogonal array is used as a variable selection approach in optimizing the predictive model. …”

Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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Application of Multi-objective Genetic Algorithm (MOGA) for design optimization of valve timing at various engine speeds by Mohiuddin, A. K. M., Rahman, Mohammed Ataur, Haw Shin, Yap

“…The GT-Power model is run simultaneously with mode Frontier to perform multiobjective optimization.…”
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Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm by Hannan M.A., Akhtar M., Begum R.A., Basri H., Hussain A., Scavino E.

Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

“…Computer A will be sent the data to computer B through the internet/LAN using JAVA program. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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