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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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5
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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6
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…For most of the cases of the shortest route finding, the Dijkstra's algorithm is known to be an optimal search algorithm. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…The results obtained are analysed using the ratio of satisfied clause (RSC), the root means square error (RMSE), and CPU time. The simulated results suggest that the proposed algorithm is effective in doing MAX2SAT logic programming by analysing the performance by obtaining lower Root Mean Square Error, high ratio of satisfied clauses and lesser CPU time.…”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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Ensemble deep learning approach for apple fruitlet detection from digital images
Published 2024“…To enhance the overall performance of the model, the revised CNN-based YOLOv5 ensemble model was implemented with the Sigmoid Linear Unit (SiLU) activation function, Batch Normalization, and SGD optimization algorithms. The combination of activation function, optimization, batch normalization, and ensemble technique are later used to enhance the YOLOv5 ensemble model with the benefits of utilizing limited resources. …”
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Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…The first technique is to encode the logic programming in radial basis function neural networks. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Following the success, this study has integrated the two algorithms to better optimize the LSSVM. The newly proposed forecasting algorithm, termed as CUCKOO-BAT-LSSVM, produces better forecasting in terms of MAPE, accuracy and RMSPE. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
Published 2008“…However, the standard FCM algorithm takes a long time to partition a large dataset. …”
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Projecting image on non-planar surface with zero-th order geometric continuity using simple dual-linear function and manipulation of strict integer implementation in programming la...
Published 2015“…Usage of a projection system to display large screen images is still relevant in the midst of LED-based display increasing popularity.This is due to that the system itself is a mature technology, reliable and cheaper than the LED counterpart.While various methods had addressed the projection problems on curve surface, projecting image on jagged like surface (zero order geometric continuity) has yet to be studied in depth.This paper proposes a method for projecting image on non-planar surface with zero-order geometric continuity property using parametric modeling.The method manipulate linear function by combining two functions into one by taking advantage of computer programs strict implementation of integer variables.The method was applied to grid-based texturing algorithm in order to create the desired zero-continuity effect on the surface.The method was compared with texturing that implement existing curve algorithm to project image on the screen.Visual evaluation results showed that the proposed method fared better compared to existing curve-based projection algorithm.…”
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A Novel Hybrid Harris Hawk-Arithmetic Optimization Algorithm for Industrial Wireless Mesh Networks
Published 2023“…The HHAOA algorithm was evaluated on various benchmark functions and compared with other optimization algorithms, namely Arithmetic Optimization Algorithm, Moth Flame Optimization, Sine Cosine Algorithm, Grey Wolf Optimization, and Harris Hawk Optimization. …”
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