Search Results - (( re evaluation model algorithm ) OR ( parameter information based algorithm ))*
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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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2
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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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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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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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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7
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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Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…Nonetheless, the optimal parameter settings for the watershed algorithm need to be adjusted based on stand density. …”
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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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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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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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The effect of GA parameters on the performance of GA-based QoS routing algorithm
Published 2023Conference paper -
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PSAT : a pairwise test data generation tool based on simulated annealing algorithm
Published 2015“…In this research, the test case will be generated based on the SA algorithm to show that the test case can be generated with sufficient.…”
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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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Sequence-based interaction testing implementation using Bees Algorithm
Published 2023Subjects: “…Bees Algorithm…”
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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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Self-adaptive Population Size Strategy Based on Flower Pollination Algorithm for T-Way Test Suite Generation
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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