Search Results - (( programming problem prediction algorithm ) OR ( java application learning algorithm ))
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Predictive Analytics in Genetic Engineering as an Optimization Problem
Published 2024“…Such predictive analytics information is useful for guiding decision-making by researchers and breeders in the crop improvement program.…”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Predicting uniaxial compressive strength using Support Vector Machine algorithm
Published 2019“…This paper presents the application of Support Vector Machine (SVM) algorithm to predict the UCS. An algorithm has been tested on a series of rock data using dry density and velocity parameters. …”
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REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION
Published 2006“…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
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Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…The result implies a good connection between how a novice programmer goes through a programming problem and his/her emotional arousal at that moment. …”
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Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm
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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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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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Green inventory routing problem using hybrid genetic algorithm / Huda Zuhrah Ab Halim ... [et al.]
Published 2021“…The mixed-integer linear programming of this problem is adopted from Cheng et al. wherein this study a different Hybrid Genetic Algorithm is proposed at mutation operator. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…One of the main problems of this method is premature convergence and to improve this problem, the compound of the particle swarm algorithm and genetic algorithm were evaluated. …”
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Building customer churn prediction models in Indonesian telecommunication company using decision tree algorithm
Published 2023“…Customer churn has become a big problem for telecommunication companies. Preventive efforts are needed by predicting the value of churn in the future. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments
Published 2017“…Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
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