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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The newly proposed algorithm was tested using a set of standard benchmark functions with different searching space and global optima placement. …”
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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 NARX algorithm is used for the modelling of Hg2+ removal. …”
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3
Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
Published 2021“…In conclusion this paper is to develop a product recommender in marketplace mobile application using Collaborative Filter and the accuracy of the algorithm is measured using Mean Absolute Error…”
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4
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…Subsequently, the THF modelling scheme can be incorporated into an established real time NLFXLMS algorithm termed THF-NLFXLMS algorithm. The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
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5
Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Additionally, the effect of signal weighting function is investigated further using multiple K values of K nearest neighbour (KNN) algorithm. …”
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The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga
Published 2016“…We also compared the performance of pdAPSO and pdPSO with 9 state of the art PSO algorithms using 12 benchmark functions. Our proposed algorithms have mean dependability of 80.4% for pdAPSO and 69.69% for pdPSO. …”
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7
Extensions to the K-AMH algorithm for numerical clustering
Published 2018“…The clustering performance of the two algorithms was evaluated on six real-world datasets against a benchmark algorithm, the fuzzy k-Means algorithm. …”
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Performance comparison of THF-NLFXLMS and VFXLMS algorithms for Hammerstein NANC
Published 2016“…Despite similar performance, this algorithm is more advantageous than the Nonlinear Filtered-X Least Mean Square (NLFXLMS) due to the use of tangential hyperbolic function (THF) instead of scaled error function (SEF) which allows the degree of nonlinearity to be modeled. …”
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Performance comparison of LFXLMS, MOVFXLMS and THF-NLFXLMS algorithms for Hammerstein NANC
Published 2016“…Filtered-X least mean square (FXLMS) algorithm is widely used in active noise control (ANC) systems when the secondary path is linear. …”
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10
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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11
A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Moreover, GRBF trained by the new algorithm has an apparent statistical meaning. Experimental results show potentials for real-life applications.…”
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Proceeding Paper -
12
Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. …”
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A modified π rough k-means algorithm for web page recommendation system
Published 2018“…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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15
Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity
Published 2012“…Furthermore, the modeling of the THF can be realized using least mean square (LMS) algorithm and utilized in the NLFXLMS control scheme. …”
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Levy tunicate swarm algorithm for solving numerical and real-world optimization problems
Published 2022“…We took advantage of Levy flight, which solved the local optima problem and improved traditional TSA efficiency. The proposed LTSA algorithm performance was evaluated using 23 well-known benchmark test functions, namely unimodal benchmark functions, multimodal benchmark functions, and fixed-dimension multimodal benchmark functions, as well as compared with the traditional TSA. …”
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A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
Published 2007“…The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm.…”
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Book Section -
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An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…First, the types of activation functions used in the hidden layer of the WNN were varied. …”
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19
Logic Programming In Radial Basis Function Neural Networks
Published 2013“…In this thesis, I established a new method for determining the best number of the hidden neurons in radial basis function neural networks. To do that I used the root mean square error function and Schwarz bayesian criterion as model selection criteria. …”
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20
Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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