Search Results - (( oil extraction mining algorithm ) OR ( spider optimization based algorithm ))*

Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Speed control of wheeled mobile robot by nature-inspired social spider algorithm-based PID controller by Khan, Huma, Khatoon, Shahida, Gaur, Prerna, Abbas, Mohamed, Saleel, Chanduveetil Ahamed, Khan, Sher Afghan

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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…The reflectance data of different wavelength bands incidence from 8 LED modules upon the oil palm FFB, were extracted by 4 different sensors of a spectrometer in laboratory experiment, for onward detailed analysis with machine learning algorithms in WEKA data mining tool. …”
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Algorithms based on spider daddy long legs for finding the optimal route in securing mobile ad hoc networks by Ghathwan, Khalil Ibrahim

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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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Classification of stock market index based on predictive fuzzy decision tree by Khokhar, Arashid Hafeez

“…After constructing predictive FDT, Weighted Fuzzy Production Rules (WFPRs) are extracted from predictive FDT, and then more significant WFPR’s are mined by using similarity-based fuzzy reasoning method. …”
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Event Detection and Information Extraction Strategies from Text: A Preliminary Study Using GENIA Corpus by Abdullah, M.H.A., Aziz, N., Abdulkadir, S.J., Akhir, E.A.P., Talpur, N.

“…However, data that are present in an unstructured form such as text documents are difficult to be processed by conventional machine learning algorithms. Therefore, in this study, we attempted to perform information extraction from textual data using current and state-of-the-art models to understand their working mechanisms. …”
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Event Detection and Information Extraction Strategies from Text: A Preliminary Study Using GENIA Corpus by Abdullah, M.H.A., Aziz, N., Abdulkadir, S.J., Akhir, E.A.P., Talpur, N.

“…However, data that are present in an unstructured form such as text documents are difficult to be processed by conventional machine learning algorithms. Therefore, in this study, we attempted to perform information extraction from textual data using current and state-of-the-art models to understand their working mechanisms. …”
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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

“…The backscattering value of each tree was then extracted from the ALOS PALSAR-2 image. Using the Extract Multi Values tool in ArcGIS, the backscattering value for each oil palm point was derived from the processed ALOS PALSAR-2 image. …”
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ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models by Ong, Song Quan, Nathan Pinoy, Lim, Min Hui, Kim Bjerge, Francisco Javier Peris-Felipo, Rob Lind, Jordan P. Cuff, Samantha M. Cook, Toke Thomas Høye

“…In this paper, we present a high-throughput scanner-based method for capturing images of arthropods that can be used to generate large datasets suitable for training machine learning algorithms for identification. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…In the second stage and for improvement of image processing study, support vector machine (SVM) classifier was performed on UAV and Pleiades imagery to identify early Ganoderma infected oil palms. In the first phase, spectral features and structural features were extracted for feature extraction. …”
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