Search Results - (( java application learning algorithm ) OR ( _ solution machine algorithm ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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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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Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time by Nazif, Habibeh, Lee, Lai Soon

“…The computational results indicate the effectiveness of the proposed algorithm in generating better quality solutions compared to other algorithms. …”
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Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…The selected algorithms for this paper are Artificial Neural Network, Support Vector Machine and Random Forest. …”
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Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…This paper discusses on the evaluation of machine learning algorithms in predicting CO2 internal corrosion rate. …”
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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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Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process by Deris A.M., Solemon B.

“…Electric discharges; Optimal systems; Optimization; Surface roughness; Artificial bee colonies (ABC); Artificial bee colony algorithms; Convergence rates; Electric discharge machining (EDM); Hybrid approach; Numerical applications; Optimal solutions; Surface roughness (Ra); Electric discharge machining…”

Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

“…Therefore, the work hybridizes guided genetic algorithm (GGA) with a single-based metaheuristics (SBHs) to handle the premature convergence in the genetic algorithm with the aim to escape from the local optima and improve the solution quality further. …”
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Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

“…A Pareto optimal set is a set of solutions that are non-dominated solutions frontier. …”
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Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

“…A Genetic Algorithm is successful in generating near -optimal solutions if it is able to produce o®spring during crossover that is better than the parent solutions. …”
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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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Solving single machine scheduling problem with maximum lateness using a genetic algorithm by Nazif, Habibeh, Lee, Lai Soon

“…The results showed that the proposed algorithm is generating better quality solutions compared to other variants of genetic algorithms…”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This can be achieved by simultaneously executing the selection of feature subset and tuning SVM parameters simultaneously. The algorithms are called ACOMVSVM and IACOMV-SVM. The difference between the algorithms is the size of the solution archive. …”
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Damping power system oscillation using elitist differential search algorithm in multi machine power system by Niamul Islam N., Hannan M.A., Mohamed A., Hussain S.

“…In this paper, damping power system oscillations is presented using the Elitist differential search algorithm (Elitist-DSA) in a multi-machine system. …”

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

“…The relevant operation is processed by only one of the uniform machines in that stage. Due to Non-deterministic Polynomial-time hard (NP-hard) nature of problem, in order to generate good solution in a reasonable computation time two solution methodologies are proposed. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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