Search Results - (( variable generation using algorithm ) OR ( parallel estimation mining algorithm ))

Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Zamli, Kamal Z., Alsariera, Yazan A.

“…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm by Chong K.L., Lai S.H., Ahmed A.N., Wan Jaafar W.Z., El-Shafie A.

Message based random variable length key encryption algorithm. by Mirvaziri, Hamid, Jumari, Kasmiran, Ismail, Mahamod, Mohd Hanapi, Zurina

“…Value of random number should be greater than 35 bits and plaintext must be at least 7 bits. A padding algorithm was used for small size messages or big random numbers. …”
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A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing by S. Ahmed, Bestoun

“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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Maximizing power generation in variable speed micro-hydro with power point tracking by Min Keng Tan, Norafe Maximo Javinez, Kit Guan Lim, Ahmad Razani Haron, Pungut Ibrahim, Kenneth Tze Kin Teo

“…As such, this paper aims to explore and develop a feasible maximum power point tracker (MPPT) with perturb and observe (P&O) and genetic algorithm (GA) in providing optimal power generation for variable speed micro-hydro system. …”
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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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Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

“…After that, ranking equation is used to arrange the generated classes from lightest to heaviest. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant by Bunyamin M.A., Yap K.S., Aziz N.L.A.A., Tiong S.K., Wong S.Y., Kamal M.F.

“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”

A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data by Rana, M.M., Rahman, A., Uddin, M., Sarkar, M.R., Shezan, S.A., Ishraque, M.F., Rafin, S.M.S.H., Atef, M.

“…The CVDTA algorithm deals with the hybrid photovoltaic (PV)â��battery energy storage system (BESS) to provide the peak shaving service where the capacity addition technique uses a peaking generator to minimize the peak demand. …”
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Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong by Lau, Chia Fong

“…HEA is run on the training set in order to provide insights on the relationships between input variables and the algae abundance. Performances of the rule sets are assessed using Receiving Operating Characteristic (ROC) with true positive rate. …”
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A variable combinatorial test suite strategy based on modified greedy algorithm by Homaid, Ameen A. Ba, Alsewari, Abdulrahman A.

“…This proposed will suggest a new CIT strategy based on a modified greedy algorithm (MGA) with addressing the supporting of variable strength interaction to generate a satisfactory test suite size.…”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…The algorithms are used to generate test cases for nine different Boolean expressions of different size and complexities. …”
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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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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

“…Using the microelectronic circuitries have shown reliability prove in terms of signal generation stability. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Three different scenarios are examined, such as scenario1 (SC1): used to predict daily power generation, scenario 2 (SC2): used to predict power generation for monthly prediction and scenario 3 (SC3): used to predict hydropower generation (HPG) seasonally. …”

Variable step-size hill-climbing search (VS-HCS) MPPT algorithm for hydrokinetic energy harnessing by Wan Ismail, Ibrahim, Nasiruddin, Sadan, Noor Lina, Ramli, Mohd Riduwan, Ghazali, Ilham, Fuad

“…In this paper, the Variable-Step Hill Climbing Search (VS-HCS) MPPT algorithm is proposed to solve the limitation of the conventional HCS MPPT. …”
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Optimal Long-Term Hydro Generation Scheduling of Small Hydropower Plant (SHP) using Metaheuristic Algorithm in Himreen Lake Dam by Hammid, Ali Thaeer, M. H., Sulaiman

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Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

“…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

“…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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