Search Results - (( simulation optimization method algorithm ) OR ( data normalization based algorithm ))
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1
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…While the automatic method focus on optimization which is normally computer based. …”
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Final Year Project -
2
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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Conference or Workshop Item -
3
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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4
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Conference or Workshop Item -
5
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Thesis -
6
Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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Conference or Workshop Item -
7
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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9
Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
Published 2017“…Results The method was tested with both simulated and real EEG data of 11 participants. …”
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10
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…This study is considered to be among the first to solve simultaneous problems of heteroskedastic and non-normal errors for panel data. Empirical evidence via simulation experiments and numerical data show TSHO to be persistent under zero or high level of contamination. …”
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Thesis -
11
Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with three training algorithms, namely, Standard Error Back-Propagation, Levenberg Marquardt and Resilient Back-Propagation algorithms. …”
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Thesis -
12
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…The reliability assessment of the adequacy of the generating system is normally calculated by using either analytical or simulation methods. …”
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Thesis -
13
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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Thesis -
14
Deep learning-based item classification for retail automation
Published 2025“…The CNN model was optimized for both accuracy and speed, incorporating regularization techniques such as dropout and batch normalization. …”
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Final Year Project / Dissertation / Thesis -
15
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…Simulation results for the independent testing data series showed that the model can perform well in simulating peak flows as well as base flows. …”
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Thesis -
16
Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
17
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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Thesis -
18
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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Thesis -
19
Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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20
Electrocardiogram based heart disease diagnosis using artificial intelligence
Published 2015“…After noise removal, the data from the ECG is to be acquired; for this purpose a method is devised based on DWT. …”
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