Search Results - (( intelligence based ems algorithm ) OR ( intelligence valid drops algorithm ))

EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency by Alam, M.G.R., Haw, R., Kim, S.S., Azad, A.K., Abedin, S.F., Hong, C.S.

“…A modified Viterbi, a machine-learning algorithm, is used to generate the most probable psychiatric state sequence based on such observations; then, from the most likely psychiatric state sequence, the emergency psychiatric state is predicted through the proposed algorithm. …”
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Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review by Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.

“…EMS strategies; AI-based algorithms categories, functions and hybridization; the state-of-art and future direction of AI-based algorithms and HFCEVs? …”

Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

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Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

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Energy Management Strategy (EMS) for Hybrid Electric Vehicles base on Safe Experimentation Dynamics (SED) by Muhammad Ikram, Mohd Rashid, Hamdan, Daniyal, Mohd Ashraf, Ahmad

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Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Optimization of wind energy conversion systems � an artificial intelligent approach by Koay Y.Y., Tan J.D., Koh S.P., Chong K.H., Tiong S.K., Ekanayake J.

Energy Management System For Three-Wheel Light Electric Vehicle Using Multi-Sources Energy Models by Azidin, Farid Arafat

“…A rule-based control algorithm which contains eight states in EMS is designed to control power switches and to ensure sufficient energy is delivered to the load. …”
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New Energy Management System Based on Intelligent Digital Power Monitoring by Fakharuddin, Azhar, Nik Mohd Kamil, Nik Yusof, Muhammad, Rauf, Abdalla, Ahmed N.

“…This paper introduces a new Energy Management System (EMS) based on intelligent digital power monitoring. …”
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Virtual power plant and microgrids controller for energy management based on optimization techniques by Abdolrasol M.G.M., Mohamed A., Hannan M.A.

Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment by Perumal, Thinagaran

“…The third algorithm, named as Pro-Active Intelligence algorithm has inspired autonomous action triggering for each event interoperation, using a control action statement that is generated by SOAP packets required for joint execution of tasks among heterogeneous subsystems. …”
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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

“…This artificial intelligent call admission control (CAC) was validated using a dynamic WCDMA mobile network simulator. …”

Employing Artificial Intelligence to Minimize Internet Fraud by Wong, E.S.K.

“…Today, pre-empting or preventing fraud before it happens occurs in the manual, non-computer based business transactions because of the natural intelligence of both seller and buyer. …”
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A Hybrid Soft Computing Framework for Electrical Energy Optimization by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

“…The scarcity of these resources demands a highly efficient and robust energy management system (EMS). In the recent literature, many artificial intelligence algorithms have been proposed to cater to the need for efficient and real-time decision-making. …”
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A real-time integrated fire detection and alarm (FDA) system for network based building automation by Anwar, Farhat, Islam, Rounakul, Hussain, Sabahat, Rashid, Muhammad Mahbubur, Shaikh, Zuhaib

“…Objectives: An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm, signal drop and network breakdown. This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. …”
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Farmland fertility optimization for designing of interconnected multi-machine power system stabilizer by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi, Mohd Jaffar, Mai Zurwatul Ahlam, Beiranvand, Hamzeh

“…This study describes the process of interconnected multi-machine power system stabilizer (PSS) optimization using a new intelligent technique called farmland fertility algorithm (FFA) to increase the stability of IEEE three machine nine bus power system and offset the low-frequency oscillations (LFOs) during a symmetrical 100 ms three-phase fault at bus 9. …”
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Blood cell classification using deep learning by Liaw, Mun Kin

“…As a result, the finalized model which consists of batch size of 16, learning rate of 0.0009, global pooling layer, 4 number of classes dropped to 3 number of classes and 3 dense layers achieved a testing accuracy of approximately 63% and validation accuracy of 99%.…”
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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

“…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context by Fakhar, Adila

“…The hybrid energy management algorithm-based the PLC signal was developed using the MATLAB. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…Complementary K-Means clustering grouped the data into two major clusters, indicating that a clear differentiation between economic-based and entrepreneurship-based courses in terms of student enrolment volume and approval distribution. …”
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