Search Results - (( data distribution bat algorithm ) OR ( _ pollution ((tree algorithm) OR (bees algorithm)) ))
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms
Published 2021“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Economic dispatch with environmental consideration using Honey Bee algorithm / Zaidi Faiq Mohd Noh
Published 2015“…Environmental concerns in industries shows increment in term of concerns and awareness among companies by strictest the pollutions regulation. This paper presents a Honey Bee (HB) Algorithm solution for Economic and Emission Dispatch problem in power system. …”
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Optimal economic environmental power dispatch by using artificial bee colony algorithm
Published 2024“…As an alternative, an Artificial Bee Colony (ABC) swarming algorithm is applied to solve the EEPD problem separately in the power systems on both standard IEEE 26 bus system and IEEE 57 bus system using a MATLAB programming environment. …”
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Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm
Published 2014“…In this work, new intelligent cooperative web caching approaches based on decision tree supervised machine learning algorithm are presented. …”
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Development of prediction model for phosphate in reservoir water system based machine learning algorithms
Published 2023“…Decision trees; Eutrophication; Forecasting; Learning systems; Neural networks; Phosphate fertilizers; Predictive analytics; Reservoirs (water); Stochastic systems; Support vector machines; Water pollution; Water quality; Water supply; Conventional modeling; Cross validation; Developed model; Non-point source pollution; Prediction model; Primary sources; Statistical indices; Water quality parameters; Learning algorithms…”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…The random forest outperformed other algorithms with a very high R2 of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…The random forest outperformed other algorithms with a very high R2 of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. …”
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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). A large number of attributes were discovered with the C4.5 DM algorithm, which also generated the classification model as a decision tree. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science
Published 2021“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The paper will primarily observe, visualize and anticipate pollution levels. In particular, three algorithms of Artificial Intelligence were used to create good forecasting models and a predictive AQI model for 4 distinct gases: carbon dioxide, sulphur dioxide, nitrogen dioxide, and atmospheric particulate matter. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The paper will primarily observe, visualize and anticipate pollution levels. In particular, three algorithms of Artificial Intelligence were used to create good forecasting models and a predictive AQI model for 4 distinct gases: carbon dioxide, sulphur dioxide, nitrogen dioxide, and atmospheric particulate matter. …”
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems
Published 2016“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Solar maximum power point tracking based on improved incremental conductance algorithm
Published 2025“…To address these limitations, this work proposes an incremental conductance-based resilient adaptive step-size MPPT (INC-RASS-MPPT) algorithm.…”
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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review
Published 2023“…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
Published 2016“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Classification prediction of PM10 concentration using a tree-based machine learning approach
Published 2022“…Therefore, in this study, three machine learning algorithms—namely, decision tree (DT), boosted regression tree (BRT), and random forest (RF)—were applied for the prediction of PM10 in Kota Bharu, Kelantan. …”
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Evaluation of machine learning in predicting air quality index / Abdullah Sani Abdul Rahman, Aizal Yusrina Idris and Suhaimi Abdul Rahman
Published 2023“…Three machine learning algorithms, namely Generalized Linear Model, Decision Tree and Support Vector Machine are used in this research. …”
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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction
Published 2023“…The hybrid technique has been developed by using deep learning algorithms with the structure of multiple layers (with several neurons) of CNN and LSTM. …”
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