Search Results - (( weight distribution system algorithm ) OR ( parameters evaluation bayes algorithm ))
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Sentiment analysis of domestic violence prediction using Naive Bayes algorithm / Nurulizzah Mohd Rahiman
Published 2024“…The research objectives focus on studying and applying the Naive Bayes algorithm for sentiment analysis on tweets related to domestic violence, aiming to provide insights for researchers, government agencies, policymakers, and the public and develop a prediction model using Naive Bayes algorithm to evaluate its performance. …”
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A binary archimedes optimization algorithm and weighted sum method for UFLS in islanded distribution systems considering the stability index and load priority
Published 2023“…This study proposes an under-frequency load-shedding (UFLS) scheme based on a binary Archimedes Optimization Algorithm (BAOA) and the Weighted Sum Method (WSM) to maintain the stability of an islanded distribution system. …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…Moreover, the empirical results obtained showed that incorporating the AHP into Firefly Algorithm improved the accuracy of weight calculations in the multi-objective formulation of the optimisation process. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a good tuning method in the hydraulic positioning system.…”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems
Published 2019“…This research aimed to reduce total power losses and improve voltage profiles of the distribution system by proposing a practical swarm optimizion algorithm GA genetic algorithm to optimize DG size and location by taking into consideration increase number of DG units in the system. …”
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Redundancy allocation for a high security control system using estimation of distribution algorithm
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Design and development of prototype robot gripper for object weight measurement
Published 2014“…Therefore, this study has proposed a robotic gripper prototype with a new configuration of pressure sensor distribution, based on development of grasping algorithm for object’s weight measurement. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
Published 2023“…From the evaluation, Naïve Bayes classifier with unigram features along with Laplace (Alpha) Smoothing Parameter achieves the best results performance in this study. …”
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Improved gravitational search algorithm for optimal placement and sizing of distributed generation for power quality enhancement
Published 2017“…DG units play a significant role in distribution system stability and to enhance its power quality. …”
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.…”
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A novel LTE scheduling algorithm for green technology in smart grid
Published 2015“…SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. …”
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IoT-based Machine Learning Comparative Models of Stream Water Parameters Forecasting for Freshwater Lobster
Published 2024“…Previously, ARIMA, Neural Network Autoregressive (NNETAR), and Naïve Bayes, were run and evaluated in R Studio to identify the best algorithm for stream analytics. …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of DG in distribution network
Published 2022“…Distributed generation (DG) can be beneficially allocated in distribution power systems to improve the power system's efficiency. …”
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Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method
Published 2016“…There are numerous advantages that can be obtained when Distributed Generation (DG) is integrated into the distribution systems. …”
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Selection of access network using cost function method in heterogeneous wireless network
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet ML-ADR classifier model performance evaluation with the highest kappa statistic value of 0.991, the lowest mean absolute error value of 0.0009, weighted average precision values of 99.2 %, ROC area coverage of 100 %, the most down trip decision time of 10 ms better than the existing 20 ms for conventional ADR. …”
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Web cluster load balancing via genetic-fuzzy based algorithm
Published 2007“…Based on the load-weight index, the genetic-fuzzy algorithm is applied to equally redistribute the workload among in the servers. …”
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