Search Results - (( _ evaluation method algorithm ) OR ( re evaluation method algorithm ))
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1
Segmentation of MRI brain images using statistical approaches
Published 2011“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…This problem remains an active area of research and, to the authors' knowledge, has not been adequately addressed by the WOA algorithm. The method was evaluated using real-world data from the first semester of 2023/2024 for faculties at the Universiti of Sarawak, Malaysia. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…This problem remains an active area of research and, to the authors’ knowledge, has not been adequately addressed by the WOA algorithm. The method was evaluated using real-world data from the first semester of 2023/2024 for faculties at the Universiti of Sarawak, Malaysia. …”
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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 best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj
Published 2023“…As such, this thesis proposes a hybrid metaheuristic method that consists of Sperm Swarm Optimization (SSO) algorithm and Genetic Algorithm (GA), which is termed HSSOGA. …”
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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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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan
Published 2018“…We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan
Published 2018“…We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). …”
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Statistical analysis on enhanced 3D-AES block cipher cryptographic algorithm / Nor Azeala Mohd Yusof
Published 2021“…These two new functions are based on the confusion method proposed by Shannon’s theory since 1945. The randomness of Enhanced 3D-AES then is re-evaluated and it has passed all 15 statistical tests for all seven data categories. …”
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10
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. …”
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11
Retinal image blood vessel extraction and quantification with Euclidean distance transform approach
Published 2020“…The significantly high accuracy in this newly developed vessel diameter quantification algorithm indicates excellent potential for further development, evaluation, validation, and integration into ophthalmic diagnostic instruments.…”
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Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems
Published 2016“…The recorded values are evaluated by a designed and tuned multi-layer feed forward neural network and the fault distances from the source are estimated accordingly. …”
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Classification of Learner Retention using Machine Learning Approaches
Published 2021“…The performance of these algorithms was evaluated based on accuracy, precision, recall, and f-measure. …”
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TDMA scheduling analysis of energy consumption for iot wireless sensor network
Published 2019“…The major objective for this project is to re-implement the proposed Energy Topology DRAND (E-T-DRAND) algorithm in IoT WSN using time slot allocation method and allocate nodes together with the node energy information and compare the obtained results with the corresponding results in the base paper. …”
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…In this research, physical and chemical influent characteristics from 2011 to 2013, including flow rate, biochemical oxygen demand (BOD), chemical oxygen demand (COD), Ammoniacal Nitrogen (NH3-N), pH, oil and grease (OG) and suspended solids (SS) of three sewage treatment plants, STP A, STP B, and STP C, in Kuala Lumpur were evaluated. Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The goodness of this ordering is measured using Average Percentage of rate of Faults Detection (APFD) metric to evaluate the effectiveness and efficiency of the approach. …”
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Control action based on steady-state security assessment using an artificial neural network
Published 2010“…The results are compared with other conventional methods and it reveals that an ANN can provide the required amount of generation re-dispatch and load shedding accurately and instantaneously compared to other methods. …”
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Automatic spinal deformity detection based on neural network
Published 2003“…Numerical representation of the degree of asymmetry is therefore useful in evaluating the deformity. Displacement of local centroids is evaluated statistically between the left-hand side and the right-hand side regions of the moiré images with respect to the extracted middle line. …”
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