Search Results - (( data optimization _ algorithm ) OR ( data visualization learning algorithm ))

Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail by ZhongMing, Liao, Ismail, Azlan

“…Experiments were conducted on OTB100 and VOT2018 benchmark datasets, and the experimental data obtained were analyzed to derive two visual single-target tracking algorithms with optimal tracking performance. …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management by Eugine Teh, Yin Jie, Chee Soon, Chong, Rozaimi, Ghazali, Hazriq Izzuan, Jaafar, Muhamad Fadli, Ghani, Howe Cheng, Teng, Nur Farhanah, Zulkipli, Siaw Hong, Liew

“…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli by Mohd Ramli, Mohamad Amirul Asyraf

“…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. The process begins with acquiring image data, which is categorized into four classes: nitrogen (N) deficiency, phosphorus (P) deficiency, potassium (K) deficiency, and normal. …”
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Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

“…The findings show that that student's good performance in programming courses has a visual, active and sequential learning style.…”

Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

“…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

“…This research contributes novel insights into the application of clustering algorithms in banking, proposing pragmatic solutions for efficient data analysis and campaign optimization. …”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

“…We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence by Razali, Mohd Norhisham, Hanapi, Rozita, Chiat, Lee Wen, Abdul Manaf, Syaifulnizam, Salji, Mohd Rafiz, Nisar, Kashif

“…Subsequently, we optimize machine learning sentiment classification by employing data augmentation in conjunction with feature engineering strategies, with the goal of improving the recognition of minority sentiment classes. …”
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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence by Razali, Mohd Norhisham, Hanapi, Rozita, Chiat, Lee Wen, Manaf, Syaifulnizam Abdul, Salji, Mohd Rafiz, Nisar, Kashif

“…Subsequently, we optimize machine learning sentiment classification by employing data augmentation in conjunction with feature engineering strategies, to improve the recognition of minority sentiment classes. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

“…It is observed that the ResNet101v2 model pairing up with an optimized SVM pipeline is able to achieve the best classification accuracy of 95% for training, validation and testing data.…”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…These methods present a robust system that enables fully automated identification and removal of artifacts from EEG signals, without the need of visual inspection or arbitrary thresholding. The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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Hierarchical extreme learning machine based reinforcement learning for goal localization by AlDahoul, Nouar, Htike, Zaw Zaw, Akmeliawati, Rini

“…This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. Gathering and evaluating a large amount of data is time and effortintensive. …”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri by Pedram , Tabatabaeemoshiri

“…The proposed methodology involves collecting wafer inspection data, extracting relevant features, and applying the GSSL algorithm to identify the hidden defects. …”
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HELM based Reinforcement Learning for Goal Localization by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw

“…The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. …”
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