Search Results - (( mobile evaluation bees algorithm ) OR ( wave classification system algorithm ))*

Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

“…The aim of this paper is to find the best possible route from the source to the destination based on a method inspired by the searching behaviour of bee colonies, i.e. artificial bee colony (ABC) algorithm. …”
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Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

“…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

“…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

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Biologically inspired mobile agent-based sensor network (BIMAS) by Ponnusamy, V., Low, T.J., Amin, A.H.M.

“…Simulation was conducted to evaluate the proposed mechanism and a prototype was developed to show the feasibility of mobile agent de-ployment and energy provisioning. …”
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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

“…It is a well-understood fact that the brain activity increases with the increased demand of cognition. The deep learning algorithm based on Pre-trained convolutional neural network (CNN) networks have been used as a transfer learning for the classification of rest and cognitive states and also assessed the cognitive load using brain waves particularly alpha wave. …”
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Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin by A. Jalil @ Zainuddin, Siti Zura

“…This thesis presents a novel analysis and classification of human radiation wave for gender and body segments recognition. …”
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Spectral feature selection and classification of roofing materials using field spectroscopy data by Samsudin, Sarah Hanim, M. Shafri, Helmi Z., Hamedianfar, Alireza, Mansor, Shattri

“…However, the high dimensionality of these data needs to be reduced to extract significant wave-lengths useful in roof discrimination. Therefore, this research used feature selection algorithms of the support vector machine (SVM), genetic algorithm (GA), and random forest (RF) to select the most significant wavelengths, and the separability between classes was assessed using the SVM classification. …”
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Automatic diabetic retinopathy detection and classification system by Omar, Zainab Awatif, Hanafi, Marsyita, Mashohor, Syamsiah, Mahfudz, Nur Faten Munirah, Abdul Muna'aim, Maimunah

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A Naïve-Bayes classifier for damage detection in engineering materials by Addin, O., Salit, Mohd Sapuan, Mahdi Ahmad Saad, Elsadig, Othman, Mohamed

“…The method is based on mean and maximum values of the amplitudes of waves after dividing them into folds then grouping them by a clustering algorithm (e.g. k-means algorithm). …”
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Real time power quality event detection using continuous wavelet transform by Tan R.H.G., Ramachandaramurthy V.K.

Evaluation of time-domain features for motor imagery movements using FCM and SVM by Khorshidtalab, Aida, Salami, Momoh Jimoh Eyiomika, Hamedi , Mahyar

“…BMIs aim to translate brain activities into control commands. To design a system that translates brain waves and its activities to desired commands, motor imagery tasks classification is the core part. …”
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Evaluating the effectiveness of time-domain features for motor imagery movements using SVM by Khorshidtalab, Aida, Salami, Momoh Jimoh Emiyoka, Hamedi , Mahyar

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Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

“…Medium tree, Gaussian Naive Bayes and Ensemble Subspace k Nearest Neighbour algorithms are used for classification performance comparison. …”
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Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms by Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

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Analysis of algorithms variation in multilayer perceptron neural network for agarwood oil qualities classification by Nurul Shakila, Ahmad Zubir, Mohamad Aqib Haqmi, Abas, Ismail, N. A., Nor Azah, Mohd Ali, Mohd Hezri, Fazalul Rahiman, Ng, K. M., Saiful Nizam, Tajuddin

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Comparison between Levenberg-Marquardt and scaled conjugate gradient training algorithms for ionosphere condition using Multilayer Perceptrons / Mohd Sharif Ibrahim by Ibrahim, Mohd Sharif

“…Ionosphere can be described a many layer and have own functional of systems at atmosphere. This paper described the examinations of two training algorithms which are Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) of Multilayer Perceptrons (MLPs) using MATLAB R2009a. …”
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Brain computer interface design and applications: challenges and future by Alwasiti, Haider Hussein, Aris, Ishak, Jantan, Adznan

“…For many decades, instrument control by just thinking, using brain waves, has been accepted in science fiction. However, it is only in the last ten years that these systems have been shown to be feasible in laboratories. …”
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Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials by Ng, Sok Choo

“…Increasing the ultrasound system frequency can result in detection of smaller defects but the depth of penetration of the wave decreases. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…EEG signal analysis involves multi-frequency non-stationary brain waves from multiple channels. Segmenting these signals, extracting features to obtain the important properties of the signal and classification are key aspects of detecting epileptic seizures. …”
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