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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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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Hence, to enhance the search ability of Cuckoo Search, it is integrated with Bat algorithm that offers a balanced search between global and local. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…One of the nature inspired meta-heuristic Bat algorithm is becoming a popular method in solving many complex optimization problems. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…The BFO algorithm is used to create machine cells and part families. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Naive bayes-guided bat algorithm for feature selection.
Published 2013“…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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Bat algorithm for rough set attribute reduction
Published 2023“…AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine learning and signal processing. In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
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An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms
Published 2022“…The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. …”
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Natural extensions: Bat algorithm with memory
Published 2023“…Bat Algorithm (BA) has recently started to attract a lot of attention as a powerful search method in various machine learning tasks including feature selection. …”
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New modified controlled bat algorithm for numerical optimization problem
Published 2022“…Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. …”
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Naive Bayes-guided bat algorithm for feature selection
Published 2023“…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…While machine broken comes into account, it is found that machine unreliability can cause increasing machine-load variation and strengthen the system imbalance as well. …”
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A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization
Published 2023“…agricultural market; carbon dioxide; carbon emission; Gross Domestic Product; optimization; support vector machine; Iran; carbon dioxide; algorithm; gross national product; Iran; support vector machine; Algorithms; Carbon Dioxide; Gross Domestic Product; Iran; Support Vector Machine…”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm
Published 2020“…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Least square support vector machines (LSSVM) are well suited to handle complex non‑linear power load series. …”
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Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer
Published 2023“…Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression problem; Times series; Long short-term memory…”
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Predicting uniaxial compressive strength using Support Vector Machine algorithm
Published 2019“…This paper presents the application of Support Vector Machine (SVM) algorithm to predict the UCS. An algorithm has been tested on a series of rock data using dry density and velocity parameters. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…Furthermore, the EDLB algorithm enhances load balancing by 46.46%. These results highlight the effectiveness of the EDLB algorithm in addressing critical load balancing issues and surpassing existing methods. …”
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Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm
Published 2023“…algorithm; drought; machine learning; modeling; optimization; prediction; support vector machine; water management; Iran; Euphausiacea…”
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