Search Results - (( initial solution machine algorithm ) OR ( java application learning algorithm ))
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Flexible job shop scheduling using priority heuristics and genetic algorithm
Published 2010“…In the next method, a genetic algorithm has been developed. It has been shown that proposed genetic algorithm with a reinforced initial population (GA2) has better efficiency compared to a proposed genetic algorithm with fully random initial population (GA0). …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals
Published 2015“…The BBO-VNS match-up algorithm manipulates the idle times on machines within the time horizon for assigning the affected operations by breakdown and/or newly arrived orders. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…The mass production hasn’t initiated due to the inefficiency of the process and the dependency on experts. …”
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A branch and bound and simulated annealing approach for job shop scheduling
Published 2004“…In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which will slightly perturb the initial feasible solution to decrease the makespan. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
Published 2021“…Initially, the current status of palm oil yield around the world is presented, along with a brief discussion on the overview of widely used features and prediction algorithms. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…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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Conference or Workshop Item -
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…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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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The comprehensive experiments results show that the proposed algorithm outperforms all other algorithms in terms of sentiment analysis classification accuracy through finding the best solutions, while its also minimizes the number of selected features. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.…”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Many machine learning algorithms excel at handling problems with conflicting objectives. …”
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Enhancement of feature sets for subjectivity analysis on Malay-English code-switching text
Published 2023“…The combination has consistently performed at the accuracy of 59% using both machine learning classifiers. The consistent performance indicates the combined feature sets are the viable solution for subjectivity analysis on the Malay-English code-switching text.…”
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Bottleneck-based heuristic for permutation flowshop scheduling
Published 2017“…The newly heuristic is developed by introducing the bottleneck-based concept that was applied at the beginning of initial solution determination. The heuristic is known as Bottleneck-Based (BNB) heuristic. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…However, the HKA algorithm has its own flaws. Although it was introduced as a population-based stochastic optimization algorithm, HKA is not exactly a population-based algorithm because it initializes and updates only a single solution. …”
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An artificial bee colony-based double layered neural network approach for solving quadratic Bi-level programming problems
Published 2020“…For an efficient and effective solution of such problems, the proposed potential methodology includes an improved Artificial Bee Colony (ABC) algorithm, a Hopfield Network (HN), and a Boltzmann Machine (BM). …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…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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