Search Results - (( using formulation based algorithm ) OR ( using factorization learning algorithm ))
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1
Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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2
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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3
Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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4
Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
Published 2021“…The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. …”
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5
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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6
Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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7
Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms
Published 2024“…On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. …”
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8
Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam
Published 2018“…In comparison to the other widely used conventional learning algorithms, the ELM has a much faster learning ability.…”
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9
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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10
Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron
Published 2013“…In this research, Natphoric algorithm is used in order to simulate how the experts find the significant factor of emotions. …”
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11
Super resolution imaging using modified lanr based on separable filtering
Published 2019“…Super resolution is then achieved using the regularized patch representation (projection matrix) learned to predict the high resolution image features. …”
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12
Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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13
A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation
Published 2024“…Therefore, this paper proposed a carbonyl iron particle (CIP) concentration based MRE prediction model using neural network algorithm. …”
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Combining cluster quality index and supervised learning to predict students’ academic performance
Published 2024“…The best cluster is further analysed using classification to predict students’ academic performance. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023Article -
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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq
Published 2023“…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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17
Adsorption of non-ionic surfactants on organoclays in drilling fluid investigated by molecular descriptors and Monte Carlo random walk simulations
Published 2021“…Using the Random Forests machine learning algorithm software, the non-ionic surfactant adsorption on organoclays was found to be affected mainly by the hydrophobicity and molecular shape of hydrophobic chains of non-ionic surfactants. …”
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18
Global spatial suitability mapping of wind and solar systems using an explainable aI-based approach
Published 2022“…Real-world renewable energy experiences (more than 55,000 on-site wind and solar plants worldwide) are exploited to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-layer Perceptron (MLP). …”
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POTENTIAL GROUPER FEED FORMULATION BASED ON EVOLUTIONARY ALGORITHM CONCEPT WITH A UNIQUE SELECTION OPERATOR
Published 2018“…One potential approach is the Evolutionary Algorithm (EA) which has been used to solve the feed formulation problems in poultry, shrimp and cattle. …”
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Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia
Published 2019“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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