Search Results - (( parameter optimization _ algorithm ) OR ( variable evaluation techniques algorithm ))

Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents the integration of Mixed Variable Ant Colony Optimization and Support Vector Machine (SVM) to enhance the performance of SVM through simultaneously tuning its parameters and selecting a small number of features.The process of selecting a suitable feature subset and optimizing SVM parameters must occur simultaneously,because these processes affect each ot her which in turn will affect the SVM performance.Thus producing unacceptable classification accuracy.Five datasets from UCI were used to evaluate the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with the small size of features subset.…”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…Furthermore, the utilization of FA and ABC optimization techniques facilitated the optimization of the ANN model parameters. …”

Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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Optimization of medical image steganography using n-decomposition genetic algorithm by Al-Sarayefi, Bushra Abdullah Shtayt

“…To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm by Priyadi, Irnanda, Daratha, Novalio, Gunawan, Teddy Surya, Ramli, Kalamullah, Jalistio, Febrian, Mokhlis, Hazlie

“…A novel approach utilizing the Modified Sine Cosine Algorithm (MSCA), a nature-inspired metaheuristic optimization technique, is proposed to resolve (N-1) contingency rankings efficiently. …”
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Solving SVM model selection problem using ACOR and IACOR by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In applying ACO for optimizing SVM parameters which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretize process would result in loss of some information and hence affect the classification accuracy.In order to enhance SVM performance and solving the discretization problem, this study proposes two algorithms to optimize SVM parameters using Continuous ACO (ACOR) and Incremental Continuous Ant Colony Optimization (IACOR) without the need to discretize continuous value for SVM parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed integrated algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM. …”
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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Incremental continuous ant colony optimization technique for support vector machine model selection problem by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This study proposes an algorithm that can optimize Support Vector Machine parameters using Incremental Continuous Ant Colony Optimization without the need to discretize continuous value for support vector machine parameters.Seven datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithmin terms of classification accuracy.Promising results were obtained when compared to grid search technique.…”
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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

“…We detail the design of this combined algorithm and evaluate it through experiments on multiple synthetic and benchmark problems. …”
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Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

“…To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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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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Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA by Sajjadi, B., Davoody, M., Abdul Raman, Abdul Aziz, Ibrahim, Shaliza

“…Besides, the numerical optimization technique was employed to optimize process variables in order to obtain the maximum FAME content (reaction yield) along with the best properties using both RSM and ANN-GA techniques. …”
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Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

“…In this algorithm, the user has to tune an appropriate variable which directly affects the power consumption and the data gathering latency. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

“…It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. For example, Tabu Search (TS) has been successfully hybridized with other techniques, including particle swarm optimization (PSO) algorithm and the two-stage TS algorithm to solve MKP. …”
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PID-PSO DC motor position controller design for ankle rehabilitation system by Azizi, Muhammad Azizul Raziq

“…The transfer function is a model in Matlab software to validate the performance of the control system through simulation compared with real-time experiments. Next, the control algorithms are proposed to design and implement the Proportional-Integral-Derivative (PID) with Particle Swarm Optimization (PSO) controller technique for optimal Proportional (Kp), Integral (Ki) and Derivative (Kd) gains. …”
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Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance by Uddin M.N., Amin I.K.

Evaluation of lightning return stroke current using measured electromagnetic fields by Mahdi, Izadi

“…This research proposed an inverse procedure algorithm using the proposed general fields’ expressions and the particle swarm optimization algorithm (PSO) in the time domain where the full channel base current wave shape in time domain can be determined. …”
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