Search Results - (( using function _ algorithm ) OR ( parameter optimization ((svm algorithm) OR (bat algorithm)) ))

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm by Mohd Annuar, Khalil Azha, Selamat, Nur Asmiza, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham

“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem by Mohd Said, Rahaini, A Aziz, Khairul Azha, Zainal Abidin, Amar Faiz, Mat Jizat, Jessnor Arif, Mohd Khairuddin, Ismail, Widiyanto, Sigit, Abdul Waduth, Mohamed Faisal

“…In camera auto calibration, the major goal is to discover intrinsic parameter values that minimize the cost function. This study proposes to implement Bat algorithm, a stochastic optimization technique, to determine the optimum intrinsic parameter values. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique by Lee, Zhong Zhen, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Abraham, Ajith

“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Support vector machine and neural network based model for monthly stream flow forecasting by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

“…Heuristic optimization namely PSO and BA are introduced to find the optimum SVM and BPNN parameters. …”

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

“…The method has been optimized with the best parameters selected; c = 100, E = 10-6 and ex = 2 for non linear kernel function. …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…The combination of these two aspects can assist to balance and enhance the exploration and exploitation capability. Before using the JAABC5ROC as an optimizer for the SVM, a total of 10 benchmark function were used to determine its performance assessment 5 common benchmarks which are (Shows Rosenbrok, Sphere, Step and RS Schwefel Ridges and RS Zekhelip) and 5 CEC2017 benchmarks which are (Shifted and Rotated Zakharov Function, Hybrid Function 01, Composite Function 08, Composite Function 09 and Composite Function 10). …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…The first two algorithms, ACOR-SVM and IACOR-SVM, tune the SVM parameters while the second two algorithms, ACOMV-R-SVM and IACOMV-R-SVM, tune the SVM parameters and select the feature subset simultaneously. …”
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Biochar production from valorization of agricultural Wastes: Data-Driven modelling using Machine learning algorithms by Kanthasamy, R., Almatrafi, E., Ali, I., Hussain Sait, H., Zwawi, M., Abnisa, F., Choe Peng, L., Victor Ayodele, B.

“…The artificial neural network-based algorithms outperformed the SVM and GPR as indicated by the R2 > 0.9 and low predictive errors. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”

Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Comparison performances between MABSA-PI controller and MABSA-PD controller for DC motor position system by Mohamad Harith Hilmi, Fajaffri, Nafrizuan, Mat Yahya

“…Modified adaptive bats sonar algorithm (MABSA) will be implemented in the PI controller and PD controller as the main algorithm. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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