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1
Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…Our results show that algorithms which use elitism feature are superior to other algorithms in most of the metrics. …”
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Thesis -
2
Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…The accuracy from the selected most optimized models were 100%. The selected most optimized models were then can be used to classify between clean water and polluted water based on capacitance input.…”
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Student Project -
3
One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. …”
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4
Optimal Placement of Phasor Measurement Unit (PMU) using genetic algorithm & cuckoo search algorithm
Published 2025“…The IEEE 57-bus test system is used as the benchmark model for algorithm evaluation. …”
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Proceeding Paper -
5
An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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6
Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…Selecting the relevant features from the data leads to better classification results. Optimization algorithms are successfully applied in the feature selection task in many systems. …”
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7
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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8
Voting algorithms for large scale fault-tolerant systems
Published 2011“…In this research, we proposed optimal algorithms using Divide and Conquer, Brent’s theorem and parallel algorithms, appropriate for today’s large scale systems such as satellite processing systems, traffic control, weather forecasting which all face a large quantity of processing input data. …”
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9
Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In this research, Cuckoo Search Spring Algorithm (CSSA) is proposed to enhance the robustness of algorithm by constructing the optimal network reconfiguration consist of reducing power losses and improve voltage profile with the various loadability factor as the constraint according to load profile, based on single and multiobjective model. …”
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10
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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11
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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Article -
12
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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13
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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Conference or Workshop Item -
14
An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. …”
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Article -
15
An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. …”
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16
Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Such approach is highly dependable on the clustering algorithm parameterization, and is not capable to deal with the normal system’s specification changes. …”
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17
Normalized Relational Storage for Extensible Markup Language (XML) Schema
Published 2011“…Approach: In this study we present an algorithm for generating an optimal design for XML in relational setting. …”
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Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
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19
SVM for network anomaly detection using ACO feature subset
Published 2016“…This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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Conference or Workshop Item -
20
Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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