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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…To our knowledge, there is still no implementation of machine learning models on green building valuation features for building price prediction compared to conventional building development. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil
Published 2021“…In addition, this research also develops price prediction model using Machine Learning Model based on green building datasets covering the District of Kuala Lumpur, Malaysia. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models
Published 2024“…Using the extreme gradient boosting (XGBoost) algorithm, which is at the forefront of machine learning algorithms, this study comprehensively examines the impact of CEO and chairman characteristics on corporate green innovation. …”
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Testing the use of machine learning for heritage property valuation / Junainah Mohamad, Nur Shahirah Ja’afar and Suriatini Ismail
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Green building factor in machine learning based condominium price prediction
Published 2022“…To predict a housing price, a robust approach is crucial, which can be effectively gained from the machine learning technique. As research on green building with machine learning techniques is rarely reported in the literature, this paper presents the fundamental design and the comparison results of three machine learning algorithms namely deep learning (DL), decision tree (DT), and random forest (RF). …”
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Utilizing RGB Imaging and Machine Learning for freshness level determination of green bell pepper (Capsicum annuum L.) throughout its shelf-life
Published 2025“…The models demonstrated exceptional accuracy in classifying and predicting the freshness of green bell peppers on the storage day, achieving 100 % accuracy with the neural network algorithm.…”
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Classification of Unhealthy Chicken based on Chromaticity of the Comb
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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar
Published 2020“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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Fault classification in smart distribution network using support vector machine
Published 2023Article
