Search Results - (( developing integration svm algorithm ) OR ( java implication tree algorithm ))

Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia by Ansari, Mozafar, Othman, Faridah, Abunama, Taher, El-Shafie, Ahmed

“…The integrated model developed includes the NAR model for low and average influent and the SVM model for peak inflow.…”
Get full text
Get full text

Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
Get full text
Get full text

AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm by Salim, Nur Saadah, Saad, Shahadan

“…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
Get full text
Get full text
Get full text

Classification of hand gestures from EMG signals / Diaa Albitar by Albitar, Diaa

“…This integration will help on the development of control strategy of the prosthetic hand.…”
Get full text
Get full text

Polycystic Ovary Syndrome (PCOS) prediction system using PSO-SVM / Lukman Hakim Shaufee, Hamidah Jantan and Ummu Fatihah Mohd Bahrin by Shaufee, Lukman Hakim

Get full text
Get full text

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. …”
Get full text
Get full text
Get full text
Get full text

Support vector machine in precision agriculture: a review by Kok, Zhi Hong, Mohamed Shariff, Abdul Rashid, M. Alfatni, Meftah Salem, Bejo, Siti Khairunniza

“…To our knowledge, this review highlights and summarizes recently renewed efforts of improving SVM performance in PA through its integration with DL, which is believed to be an upcoming trend for ML model development in modern PA.…”
Get full text
Get full text

Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…In this study, different supervised and unsupervised machine learning algorithms are proposed: artificial neural network (ANN), AutoRegressive Integrated Moving Aveage (ARIMA) and support vector machine (SVM). …”

Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…These findings demonstrate that integration of ML with GHBD significantly improved predictive capabilities, enabled real time application, reduce experimental effort, as well as improve the development of intelligent, sustainable, and scalable water treatment technology. © 2025 Elsevier B.V.…”
Get full text
Get full text

SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

Get full text
Get full text

New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

“…To enhance the SVM performance, an outstanding hybrid Artificial Immune Least square Support Vector Machine (AILSVM) that integrates SVM with Artificial Immune System (AIS) was introduced in voltage stability prediction. …”
Get full text
Get full text

Development of track-driven agriculture robot with terrain classification functionality / Khairul Azmi Mahadhir by Mahadhir, Khairul Azmi

“…A test bed equipped with a tracked-driven robot and three types o f terrain i.e. sand, gravel and vegetation has been developed. A small and low power MEMS accelerometer is integrated into the robot for measuring the vertical acceleration. …”
Get full text
Get full text

Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

“…However, current models often rely on coarse regional data and fail to account for microclimatic variations, limiting their predictive accuracy in dengue hotspots. This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
Get full text
Get full text
Get full text

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
Get full text
Get full text

Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

“…Four classification algorithms specifically the Cubic SVM (C.SVM), Quadratic SVM (Q.SVM), Ensemble Bagged Trees (EBT) and k-Nearest Neighbor (kNN) are employed to test the classification accuracy. …”
Get full text
Get full text
Get full text

Intelligent decision support systems: transforming smart cities management by Ahmed, Zeinab E., Hassan Abdalla Hashim, Aisha, Mokhtar, Rania A., Saeed, Mamoon M.

“…A comparison of the energy used by promised by these algorithms including LSTM, SVM, KNN, and the OPTIMUS, a system is developed that enables smart cities to significantly save energy hence highlighting its efficiency. …”
Get full text
Get full text
Get full text
Get full text

Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
Get full text
Get full text

Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Results have shown that integrated Cuckoo search and induced SVM learning algorithm produced the best-selected feature subset with 99% coefficient of determination, lowest RMSE and MAE of 0.081 and 0.0132 respectively.…”
Get full text
Get full text

Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text