Search Results - (( solution solution learning algorithm ) OR ( program implementation mining algorithm ))
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Problem restructuring in interger programming for reduct searching
Published 2003“…They can describe the whole information system when implementing discernment. In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Article -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Nonetheless, OBL-based solutions often consider one particular direction of the opposition. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…Machine learning is an implementation of artificial intelligence (Al) that allows systems to learn and build on knowledge without being directly programmed automatically. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications
Published 2020“…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
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Conference or Workshop Item -
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…Using these C values would make those non-selected Q values more competitive in order to achieve updated and more reliable values. The CDRQ Routing Algorithm provides a solution to the problem addressed above by integrating the advantages of CQ Routing Algorithm and Dual Reinforcement Learning. …”
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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…To find the optimal solution for the multiple disc clutch design, the Bees Algorithm will be used and expected to give better result compared to other optimisation algorithms that already have been used.…”
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Data mining techniques for transformer failure prediction model: A systematic literature review
Published 2023Conference Paper -
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Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines
Published 2019“…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO 2 internal corrosion rate. …”
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Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines
Published 2019“…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO2 internal corrosion rate. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Finding a good classification algorithm is an important component of many data mining projects. …”
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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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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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Proceeding Paper -
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…It was shown that our proposed model exhibits stronger search ability compared to other metaheuristic algorithms and Exhaustive Search. Our model enhanced the efficiency of the learning phase, resulting in the number of global solutions accounting for 100 %, and significantly improved the global solution diversity. …”
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Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
Published 2024Subjects:Conference Paper -
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