Search Results - (( data extraction method algorithm ) OR ( using solution learning algorithm ))

APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

“…The Self-Training algorithm greatly benefits semi-supervised learning which allows classification of entities given only a small-size of labelled data. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

“…The SVM algorithm has been used to detect high- and low-density vegetation regions from the extracted ROI. …”

Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review by Aliyu, R., Mokhtar, A.A., Hussin, H.

“…Data models can be trained using machine learning and statistical ideas, employing condition data and on-site feedback. …”
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Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data by Qaedi, Kasyful, Abdullah, Mardina, Yusof, Khairul Adib, Hayakawa, Masashi, Zulhamidi, Nur Fatin Irdina

“…However, the complexity of the data has made it difficult to create an accurate model for EQ prediction using this method. …”
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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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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel by Usmani, U.A., Happonen, A., Watada, J.

“…We propose a clothing segmentation framework having novel feature extraction and fusion modules. The low-level feature data are extracted by the feature extraction module using Mask Region Convolutional Neural Network (RCNN) segmentation branches and Inception V3 used to extract the high-level semantic data. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The IncFRNN algorithm updates the training set by employing a heuristic update method to maintain representative objects and eliminate rarely used objects. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…We conduct descriptive analytics to explore and extract a summary of data for initial understanding. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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An enhancement of age and gender classification accuracy with hybrid handcrafted and deep features using hierarchical extreme learning machine / Mohammad Javidan Darugar by Mohammad Javidan , Darugar

“…Our proposed architecture consists of two main categories of feature extraction and learning methods which are namely supervised and unsupervised. …”
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Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

“…A possible solution is to employ an intelligent middleware that can analyze both the human-generated data and sensory generated data. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

Effective source number enumeration approach under small snapshot numbers by Ge, Shengguo

“…To verify the performance of the proposed SEMD method, this study designs a series of experiments, using theoretical data and measured data from a radio frequency anechoic chamber laboratory as research objects. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Refinement of generated weighted fuzzy production rules by using fuzzy neural networks for stock market prediction. by Md. Sap, Mohd. Noor, Khokar, Rashid Hafeez

“…In this paper, we look into the solutions of the above problems by 1) enhancing the representation power of WFPRs by including local and global weights, 2) developing a fuzzy neural network (FNN) with enhanced learning algorithm, and 3) using this FNN to refine the local and global weights of WFPRs for stock market prediction. …”
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Prediction of fruit ripening by Artificial Neural Network based on relationship between pectin and image analysis / Aisyah Sakina Shahrin ... [et al.] by Shahrin, Aisyah Sakina, Osman, Mohamed Syazwan, Ramli, Rafidah Aida, Setumin, Samsul, Senin, Syahrul Fitry

“…The models used is MLP model with back-propagation algorithms with the help of learning function of Bayesian regularization and the transfer function is tangent hyperbolic. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…In an imbalanced dataset, one of the two classes contains fewer total samples than the other class. The sampling-based method, also known as the data level method, is used to deal with this problem. …”
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