Search Results - (( based optimization method algorithm ) OR ( parameter extraction learning algorithm ))

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.

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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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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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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. …”

A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks by Azeez, Omer Saud, M. Shafri, Helmi Z., Alias, Aidi Hizami, Haron, Nuzul Azam

“…A Bayesian technique was used to find the best parameters for the multiresolution segmentation (MRS) algorithm while the CNN model learns the image features at different layers, achieving joint optimization. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…In addition, the results also showed that the proposed hierarchical classification method could extract geometric road elements with an average error rate of 6.25% for slope parameter and 6.65% for superelevation parameter, and it is transferable to other regions of similar environments. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

“…The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. …”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…However, due to some drawbacks, an advanced technique was employed in this study. The proposed method involves using a convolutional neural network (CNN) with a feature extraction ability to learn from the hydrological dataset efficiently. …”
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…Next, an advanced machine learning based on is utilized to predict islanding and none islanding states. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…In conclusion, the supervised learning method using FRF change is convenient and effective in identifying the damage state of the plate, and can be optimized through mode shape assessment. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…Secondly, to enhance feature propagation and reduce the number of parameters, the dense network was connected after the multi-scale convolutional network, and the learning rate change function of the stochastic gradient descent algorithm was optimized to objectively evaluate the training effect. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo