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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
Published 2019“…The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. …”
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Article -
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A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption
Published 2019“…The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. …”
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Book Chapter -
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024Subjects:Article -
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Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…In the agent-based approach to middleware, the agent’s property such as autonomous, mobile and intelligent are suitable as e-assistance tool for big data management. …”
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Conference or Workshop Item -
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Novel rule base development from IED-resident big data for protective relay analysis expert system
Published 2016“…Thus, the objective of this chapter is to study the design of an Expert System called ProtectiveRelay Analysis System (PRAY), which is imbedded with a rule base construction module. This module is to provide the facility of intelligently maintaining the knowledge base of PRAY through the prior discovery of relay operations (association) rules from a novel integrated data mining approach of Rough-Set-Genetic-Algorithm-based rule discovery and Rule Quality Measure. …”
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Book Section -
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Efficient transmission based on genetic evolutionary algorithm
Published 2022“…In this paper, an energy-saving mechanism based on genetic algorithm in wireless sensor network (WSN) is proposed. …”
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Proceedings -
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Published 2018“…The limitations are addressed as challenges to obtain a set of requirements for Computational Intelligence Medical Data (CIMD) in establishing an efficient CIMD architectural design. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024Subjects:Article -
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Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks
Published 2021“…In this paper, we perform a survey of the latest research on intelligent data processing technology applied in agriculture, particularly in rice production. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
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Conference or Workshop Item -
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Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review
Published 2022“…A new model integrated with the existing Metocean data system using ML algorithms to monitor and interoperate with maximum performance is proposed. …”
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GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators
Published 2024“…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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DATA ANALYTICS FOR HOSPITAL OPERATIONS
Published 2015“…This statistical software is programmed to run multiple algorithms on the massive datasets in the mean of revealing similarities of items related to sets by focusing on the algorithm based of Market-Basket method. …”
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Final Year Project -
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Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases
Published 2022“…In this paper, we analyzed the latency from a particular client point based on the live data generated by their cloud data centers. …”
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