Search Results - (( developing parameter selection algorithm ) OR ( java application learning algorithm ))

Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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The effect of GA parameters on the performance of GA-based QoS routing algorithm by Yussof S., See O.H.

“…Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. …”

An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli by Ahmad Zulkhairi , Zulkefli

“…For HDL-C, the SCG algorithm with a testing accuracy of 76.7%, sensitivity of 95.5% and specificity of 25.0% was selected as best performing models to indicate the relationship of the bioelectrical parameters and the lipid profile parameters.…”
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

“…Overall, this comprehensive review provides valuable insights into the importance of algorithm development, optimization, and parameter selection in crop water modelling, specifically focusing on crop factors, soil factors, and weather factors.…”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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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.

“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm by Haruna, Chiroma, Herawan, Tutut, Iztok, Fister Jr, Iztok, Fister, Abdulkareem, Sameem, Shuib, Liyana, Mukhtar, Fatihu Hamza, Younes, Saadi, Abubakar, Adamu

“…The purpose of this study is to assist potential developers in selecting the most suitable cuckoo search variant, provide proper guidance in future modifications and ease the selection of the optimal cuckoo search parameters. …”
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Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm by Golshan, Abolfazl

“…The selection of optimal cutting parameters has always presented a critical quality concern in the micromachining process. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The adaptive technique for ant selection enables the parameter to adaptively change based on the feedback of the search space. …”
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Optimization of physical vapour deposition coating process parameters using genetic algorithm by Mohammad Jarrah, Mu'ath Ibrahim

“…Then, in order to optimize the coating process parameters, genetic algorithms (GAs) were used for the optimization work. …”
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ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS by Mohd Mustafa, Muhammad Izzatullah

“…However, there are some algorithmic parameters that need to be carefully selected to produce meaningful constantrate (or deconvolved) responses from these algorithms to avoid misinterpretation of the data leading to misidentification of the unknown system. …”
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