Search Results - (( using optimization method algorithm ) OR ( based identification learning algorithm ))

Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
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Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Most of the existing plant identification methods are based on both the global shape features and the intact plant leaves. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

“…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

“…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri by Pedram , Tabatabaeemoshiri

“…The method uses weighted edges to represent the likelihood of defect propagation between dies, optimized through extensive experimentation, followed by an iterative label propagation process to uncover hidden defects. …”
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Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…Our deep learning method also performs the atomic morphological operations and shadow removal based on the hue saturation value color space. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

“…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…This study proposed an integrated system for EEG signals pre-processing by using machine learning algorithms in the identification of artifactual components during the process of Wavelet-ICA. …”
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Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods by Chin, Ying Teh, Tay, Kai Meng, Chee, Peng Lim

“…Our analysis shows that even with multi-attribute monotone data, non-monotone fuzzy If- Then rules can be produced using an ad hoc method. The same observation can be made, empirically, using a system identification method, e.g., a derivative–based optimization method and the genetic algorithm. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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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.

“…This has gain the interest of power industries and utilities to apply machine learning as part of the operation. Fault identification and classification based machine learning application in power industries have gain significant accreditation due to its great capability and performance. …”

Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…The leaf features are first learned directly from the raw representations of input data using Convolutional Neural Networks (CNN), and then the chosen features are exploited based on a Deconvolutional Network (DN) approach. …”
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