Search Results - data distribution ((((factor algorithm) OR (bees algorithm))) OR (function algorithm))

Power-efficient wireless coverage using minimum number of uavs by Sawalmeh A., Othman N.S., Liu G., Khreishah A., Alenezi A., Alanazi A.

Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal by Zainal, Mohamad Izwan

“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

“…In this study, the problem of determination dengue disease factors was modeled using a neural network. The activation function in this neural network model then estimated using genetic algorithms. …”
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

“…The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. …”
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Optimal coordinated voltage control in active distribution networks using backtracking search algorithm by Hashim T.J.T., Mohamed A.

Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

“…Since it is unrealistic to have a NIRS dataset that can represent unforeseen future changes, an algorithm that can adapt existing data for new samples is worth to be investigated. …”
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Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation by Islam, Syed Zahurul, Othman, Mohammad Lutfi, Islam, Syed Zahidul

“…The communication requirement for integrating Distributed Renewable Generation (DRG) into Smart Grid (SG) is not strict, where the reliability and critical demand of data delivery are compromised due to the low-data rate and power of ZigBee. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…Additionally, algorithm followed by study area and species, were the main factors driving differences in the spatial scales identified. …”
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Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…This paper provides an overview of localization algorithms, including centralized and distributed algorithms. …”
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ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

“…ETERS utilizes the Beta distribution-based trust function because recovery of trust values under attacks is faster in Beta distribution than Gaussian and Dirichlet distribution. …”
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Peak pressure analysis of foot plantar distribution based on image processing algorithm by Sabry, Ali Hussein

“…The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. …”
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…In the first part of the thesis, distributed power control and beamforming algorithm is proposed in which users operating in the underlay mode can strategically adapt their power levels and maximize their own utilities. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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Improved tree routing protocol in zigbee networks by Al-Harbawi, Mostafa Kamil Abdulhusain

“…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function by Shehab, Mohammad Mohammad Said

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Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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