Search Results - ((regression algorithm) OR (((generation algorithm) OR (selection algorithm))))
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023Subjects:Conference paper -
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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications
Published 2024“…In academia, this study proposed an innovative SLR-MLR predictive algorithm and utilized a novel statistical approach to evaluate and select the superior predictive algorithm. …”
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Article -
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management
Published 2024Subjects:Article -
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Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices
Published 2016“…Subsequently, Auto-regressive lag one, AR(1), coupled with Valencia-Schaake (V-S) disaggregation model are applied to generate synthetic streamflow data. …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2023Subjects:Article -
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…To extract the maximum power from the PV system, the proposed BCM algorithm selects a suitable set of battery cells to charge for a particular time by referring to the forecasted PV output power. …”
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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming
Published 2024“…The analysis utilized a novel modified stacked Multiple Linear Regression- -Support Vector Regression (MLR- -SVR) algorithm, and a novel modified stacked MLR- -Support Vector Regression (MLR- -SVR) algorithm, demonstrating high predictive capability, especially in a limited dataset environment, which the algorithms’ superiority ranked utilizing modified Taguchi-based VIseKriterijumska Optimizacija I Kompromisno Resenje (Taguchi-based VIKOR) multi-criteria decision-making algorithm. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…As a result, the BR algorithm was chosen for both BOD and COD analysis as it can generate a good network that generalizes well enough by minimizing the combination of errors and weights. …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…This algorithms were selected based on previous literature review in price prediction. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm
Published 2017“…To evaluate the EANN model, 19 samples of experimental data from Zainol on the regression modelling of biogas production from banana stem waste were selected. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Total rules number, rules length and rules accuracy for the generation rules are recorded. The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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The basics of multi-layer feedforward neural networks / Nurul Aityqah Yaccob and Farizuwana Akma Zulkifle
Published 2025“…The weights are selected in the neural network framework using a "learning algorithm" that minimizes a "cost function," such as the mean squared error (MSE). …”
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Monograph -
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Predictive models for hotspots occurrence using decision tree algorithms and logistic regression.
Published 2013“…The results show that the C4.5 algorithm has better performance than the ID3 algorithm in terms of accuracy and the number of generated rules. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The algorithm searches the solution space by selecting various model structures and evaluating its fitness. …”
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