Search Results - (( intelligence system research algorithm ) OR ( intelligence based scheduling algorithm ))
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Solving university examination timetabling problem using intelligent water drops algorithm
Published 2024Subjects:Conference Paper -
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Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm
Published 2024“…IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. …”
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Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling
Published 2018“…The SDM is to make a division on the Swarm Intelligence (SI) algorithm which is to be a number of particles searching collections that properly can be regarded as divisions. …”
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Channel-aware downlink scheduling for quality of service in long term evolution network
Published 2018“…Initially, a range of constraints was defined based on a recent algorithm from the literature, namely Delay Based Weighted Proportional Fair (DBWPF). …”
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Processing time estimation in precision machining industry using AI / Lim Say Li
Published 2017“…Neural Network (NN) model is chosen as the artificial intelligence approach used in this research. Levenberg-Marquardt algorithm is used as the training algorithm. …”
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A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings
Published 2015“…The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
Published 2025“…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…Finally, the obtained results corroborate the premise of the proposed method through the enhanced accuracy compared to the existing artificial intelligence-based models. …”
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Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies
Published 2024“…In addition, the common objectives and constraints related to scheduling optimization are classified, and several optimization methods in the literature, including various intelligent algorithms, have been introduced, compared, and critically analyzed. …”
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Distance vector-hop range-free location algorithm for wireless sensor network
Published 2015“…Thus, this research has proposed two ideas. First is the intelligent nodes placement algorithm for sensor nodes in order to introduce algorithm with low complexity and low localization error. …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…Traditionally, coal fired power plant boilers are scheduled for maintenance in periods to ensure that the demand of the system is fully met and the reliability of the system is maximized. …”
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System
Published 2009“…Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. …”
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Dynamic approaches for spectrum control in cognitive radio networks
Published 2015“…Any effective cognitive system has to implement efficient sensing order scheduler to reduce spectrum probing cost. …”
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Modelling of home energy management system using heuristic optimization for sustainable energy utilization
Published 2023“…This research aims to develop an intelligent HEMS considering the Malaysian environment, electricity tariff, and home occupancy. …”
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ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets
Published 2021“…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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Proceeding Paper -
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