Search Results - (( a distribution function algorithm ) OR ( data distribution issues algorithm ))

Optimal coordinated voltage control in active distribution networks using backtracking search algorithm by Hashim T.J.T., Mohamed A.

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions by Mannan M., Roslan M.F., Reza M.S., Mansor M., Jern K.P., Hossain M.J., Hannan M.A.

“…The controller's aims include minimizing total operating costs for distributed energy resources and solving intricate constraint optimization issues with scheduling management operations. …”

An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

“…An experiment was carried out, and the results collected were analyzed using a nonparametric statistical test, the Mann-Whitney U test, which indicates the level of significance between the distributions of data collection. …”
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Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique by Lee, Zhong Zhen, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Abraham, Ajith

“…The proposed algorithm was tested on a pre-sam pled 17 years record of daily Kuala Lumpur Com posite Index (KLCI) data. …”
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Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim by Ibrahim, Mohamad Fakhrullah

“…The current manual process is labor-intensive, error-prone, and time-consuming. To overcome these issues, a system utilizing a Genetic Algorithm (GA) was developed to automate and optimize the timetabling process. …”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture by Ibrahim, Abeer Abdalla Zakaria, Hashim, Fazirulhisyam, Noordin, Nor Kamariah, Sali, Aduwati, Navaie, Keivan, Fadul, Saber Mohammed Elnour

“…The distributed multi-controller architecture approach is an emerging strategy that primarily aims to support network functions performed through the application of a control plane, to provide versatile network traffic management. …”
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Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

“…Furthermore, the estimation of entropy is an important issue in statistics and machine learning. This study estimated the Rényi and q-entropies of a power-function distribution in the presence of s outliers using classical and Bayesian procedures. …”
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Rate limiting algorithm on video traffic with Pareto traffic model in broadband network / Rafidah Samsuri by Samsuri, Rafidah

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Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution by Sayed, Amani Idris A

“…The findings demonstrate that the gamma distribution provides a good fit for modeling the transformed MIRR over a long-term investment period. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…In supervised learning, class imbalanced data set is a state where the class distribution is not uniform among the classes. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

“…We utilise the Q-Learning algorithm to compare actions, including context-based actions, to effectively detect crashes and achieve a higher code coverage.…”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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The Rise of Blockchain Internet of Things (BIoT): Secured, Device-to-Device Architecture and Simulation Scenarios by Arun Rana, Sharad Sharma, Kashif Nisar, Ag. Asri Ag. Ibrahim, Sachin Dhawan, Bhawani Chowdhry, Samreen Hussain, Nitin Goyal

“…Moving the Internet of Things to a distributed ledger system might be the most effective way to solve these issues. …”
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Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning by Kamaru-Zaman, Ezzatul Akmal

“…In the era of data-driven decision-making, managing dynamic data streams characterized by evolving data distributions and high dimensionality presents a formidable challenge for online feature selection. …”
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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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