Search Results - (( parameter estimation machine algorithm ) OR ( variable estimation using algorithm ))
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Processing time estimation in precision machining industry using AI / Lim Say Li
Published 2017“…An AI approach for processing time estimation by implementing desired input parameters and machining data is tested and completed. …”
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Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Published 2025Subjects:Article -
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms
Published 2023Article -
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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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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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust
Published 2022“…Based on the statistical nature of the dust explosions and controlling parameters, this study uses data-driven modelling approaches. …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust
Published 2022“…Based on the statistical nature of the dust explosions and controlling parameters, this study uses data-driven modelling approaches. …”
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Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel
Published 2021“…To explore its full potential, this research work provides a thorough investigation of process variables on the machining performances and surface features primarily required for processing 316L steel in the industry. …”
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Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel
Published 2021“…To explore its full potential, this research work provides a thorough investigation of process variables on the machining performances and surface features primarily required for processing 316L steel in the industry. …”
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Forecasting of meteorological drought using ensemble and machine learning models
Published 2025“…The SPI is a popular method for estimating the drought analysis and has been used everywhere at global level. …”
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Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data
Published 2023“…After the heterogeneity parameters were excluded from the model, the support vector machine with the MM estimator showed that better significant results were obtained with 2.09% outliers. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
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