Search Results - (( weight distribution _ algorithm ) OR ( re evaluation model algorithm ))
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1
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Finally, the initial partitioning is successively un-coarsened and re-refined back to the original hypergraph. These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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2
Robust Kernel Density Function Estimation
Published 2010“…To remedy this problem, Kim and Scott (2008) proposed an Iteratively Re-weighted Least Squares (IRWLS) algorithm for Robust Kernel Density Estimation (RKDE). …”
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3
Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The maximum RE obtained is 3.49%. The modelling results revealed that NARX algorithm is the best compared to the used algorithms in term of accuracy. …”
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4
State-Aware re-configuration model for multi-radio wireless Mesh Networks
Published 2017“…The proposed algorithm re-assigns channels to radios and re-configures flows’ routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. …”
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5
Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems
Published 2008“…GDF and GSF controllers are evaluated for two test cases namely “two-part-type production line” and “re-entrant production system”. …”
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6
Sustainable renewable energy resources utilization in rural areas
Published 2016“…Results obtained from the transportation model have been validated based on other RE studies in the area. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…Results obtained from the transportation model have been validated based on other RE studies in the area. …”
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8
Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…To address this problem, an investigation was conducted on the ordered weighted model of the FCOM algorithm leading to proposed enhancements by introducing the beta distribution weighted fuzzy C-ordered-means clustering (BDFCOM). …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Moreover, three improvements of EM for brain MRI segmentation are proposed, which incorporate neighbourhood information in a new manner in the clustering process. In addition, two algorithms for the post-processing of clustering results using user-interaction and the re-evaluation of boundary data in each cluster are presented. …”
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10
A hybrid grey wolf assisted-sparrow search algorithm for frequency control of RE integrated system
Published 2023“…Moreover, the robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameter, and weather intermittency of RE resources in real-time conditions. …”
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11
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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ReSTiNet: An efficient deep learning approach to improve human detection accuracy
Published 2023“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability
Published 2024“…Therefore, this thesis proposes a new systematic Satisfiability logical rule namely Weighted Systematic 2 Satisfiability that uses a weighted feature to control the distribution of the negative literals. …”
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14
Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri
Published 2024“…The data is preprocessed, labeled, and split into training and testing sets which are 80% for training and 20% for testing. The ANN model consists of three layers with ReLU and softmax activations and is trained using the backpropagation algorithm. …”
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15
ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy
Published 2023“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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16
Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia
Published 2018“…The RE results also prove that the SVM model’s frequency of errors above 10% or below − 10% was greater than the NAR model’s. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy
Published 2023“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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18
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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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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