Search Results - (( evolution optimization svm algorithm ) OR ( data normalization path algorithm ))

Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Wide area measurement system in the IEEE-14 bus system using multiobjective shortest path algorithm for fault analysis by Awalin, Lilik J., Syahirah, Abd Halim, Jafferi, Jamaludin, Nor Azuana, Ramli

“…The distances of the normal path (without simulated fault) and the new path (with simulated fault) were recorded. …”
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Restaurant locator using Djikstra Algorithm / Mohamad Aliff Hakimi Lukman Hakim by Lukman Hakim, Mohamad Aliff Hakimi

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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP). by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

“…Their ability as a colony to find paths or routes to the food sources has inspired the development of an algorithm namely Ant Colony System (ACS). …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Intelligent motion planning of a mobile robot by using convolutional neural network / Siti Asmah Abdullah by Siti Asmah, Abdullah

“…By the path reference created by A* algorithm the robot is capable in optimizing its path to reach the designated destination. …”
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A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm by Masood, Kamal

“…Interpolation scheme based on the multiaixality of stresses is suggested for the determination of coefficients of the model for different loading paths. Material parameter including stress sensitivity factor for normal or shear stress can be incorporated to improve the calibration process. …”
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Improving Channel Assignment for Vehicular Ad-hoc Sensor Network in Disaster Management System by Chiu Shoon, Sia

“…Moreover, an average of 22.91% for LTE-AIC with respect to normal LTE-A and 38.63% compared to LTE for high data rate. …”
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Deadline guarantee for scientific workflow using dynamic scheduling algorithms on IaaS clouds by Alqaisy, Sarah Abdulrahman Shukur

“…We will conduct a simulation experiment of scientific workflow algorithms with both of the algorithms mentioned above. …”
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A smart marker-based indoor navigation system by Teoh, Zhen Quan

“…The proposed system also employs algorithms to calculate the shortest path for navigation and estimate the user position for localization when the user scans a marker. …”
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Dynamics and control of underactuated systems with applications in robotics / Ahmad Azlan Mat Isa … [et al.] by Mat Isa, Ahmad Azlan

“…An ANN modal was trained using the experimentally obtained data and then used to predict the path of the passive joint that is positioned by the dynamic coupling of the active joint. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…A new mutation vector inspired by the two-opposite path (2-Opt) algorithm with adaptive mutation scalar (F ) and crossover rate (CR) control parameters were employed to enhance the exploration and exploitation phases of the proposed algorithm. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

“…Furthermore, variable databus widths are used in the data path of the proposed architecture, which leads to reducing the hardware cost and silicon area. …”
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A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN) by Ali, Mohammed Qasim

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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction by Ayman Mohammed Shaher Yafouz, Mr.

“…The hybrid technique has been developed by using deep learning algorithms with the structure of multiple layers (with several neurons) of CNN and LSTM. …”

Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System by Al_Fugara, A’kif Mohammed Salem

“…It has been found that the modeled predictions of depth and discharge matched observed data. A good agreement between the simulated and observed data was achieved for rating curves with RMSE = 0.96, 0.94, 0.95, and 0.97 at respective calibration points. …”
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