Search Results - (( location prediction model algorithm ) OR ( war classification using algorithm ))*
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. …”
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. …”
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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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Monitoring Land Cover Changes in Halabja City, Iraq.
Published 2013“…Quantitative analysis was conducted by using post-classification change detection technique. …”
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Classification model for hotspot occurrences using a decision tree method
Published 2011“…The model can be used to predict hotspot occurrences in new locations for fire prediction.…”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…Machine learning algorithms are deployed to perform sentiment classification. …”
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Location-based Solar Energy Potential Prediction Algorithm for Mountainous Rural Landscapes
Published 2013“…Location-based Solar Energy Potential Prediction Algorithm (LOSEPPA) takes as input, the geographic latitude and longitude of the location of interest to compute the Solar Irradiance Factor (SIF). …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…The first scenario is to apply inflow data as model input for predicting inflow (output). The second scenario is to apply inflow and rainfall data as model inputs to predict inflow (output). …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…The objective of this study is to propose a prediction model based on bio-inspired algorithm for talent knowledge discovery through some experiments. …”
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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok
Published 2019“…The other 11 prediction processes which utilised ANN model algorithms (fitting tool), gave R-values for all the algorithms higher than 0.900 except one algorithm equal to 0.8661, meanwhile MSE between 0.22 to 116.41. …”
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab
Published 2025“…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). …”
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Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches
Published 2024“…Using a comparison of three different major types, the best predictive model was determined. Statistical models and machine learning algorithms automatically learn and improve based on data. …”
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Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability
Published 2018“…For this aim, standalone ANFIS, ANFIS-PSO, ANFIS-GA and ANFIS-DE prediction algorithm are developed in MATLAB platform. …”
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Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction
Published 2023“…This study proposes accurate model based on Machine Learning algorithms to predict Tropospheric ozone concentration in major cities located in Kuala Lumpur and Selangor, Malaysia. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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