Search Results - (( java implementation graph algorithm ) OR ( global optimization svm algorithm ))

Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

“…Theoretically the training is guaranteed to converge to a global optimal. The training of SVM is not as straightforward as it seems. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”

Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…In the benchmark paper, the result of implementation of LACE algorithm in 400, 600, 800 and 1000 servers were plotted at different graphs. …”
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Face Recognition Approach using an Enhanced Particle Swarm Optimization and Support Vector Machine by Saad, Wasan Kadhim, Jabbar, Waheb A., Abbas, Ahmed Abdul Rudah

“…Though, there is an important issue that can affects the whole classification process which is picking the optimum parameters of SVM. Recently, Particle Swarm Optimization (PSO) is used to discover the optimal parameters of SVM and many versions of PSO are used for this purpose, like: PSO-SVM technique, opposition PSO and SVM which called (OPSO-SVM) technique and AAPSO-SVM technique which represents adaptive acceleration PSO and SVM. …”
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Sentiment analysis on COVID-19 outbreak using PSO-SVM / Amir Danial Shahrul Sazali by Shahrul Sazali, Amir Danial

“…PSO is an optimization technique by searching decision space by sharing global information between different particles. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…The SVM-JAABC5ROC outperformed all three optimizers and five classifiers in terms of accuracy for both the Wisconsin and Mammography datasets. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

“…Finally, a novel hybrid Quantum-Inspired Evolutionary Programming - Least-Squares Support Vector Machine (QIEP-SVM) was presented. The results showed that the QIEP-SVM model had shown better prediction performance as compared to classical ANN, LS-SVM and QIEP-ANN.…”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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SVM-based geospatial prediction of soil erosion under static and dynamic conditioning factors by Muhammad Raza, Ul Mustafa, Abdulkadir, Taofeeq Sholagber, Khamaruzaman, Wan Yusof, Ahmad Mustafa, Hashim, M., Waris, Muhammad, Shahbaz

“…The study implements four kernel tricks of SVM with sequential minimal optimization algorithm as a classifier for soil erosion susceptibility modeling. …”
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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Short-term PV power forecasting using hybrid GASVM technique by VanDeventer, William, Jamei, Elmira, Thirunavukkarasu, Gokul Sidarth, Seyedmahmoudian, Mehdi, Tey, Kok Soon, Horan, Ben, Mekhilef, Saad, Stojcevski, Alex

“…The GASVM model classifies the historical weather data using an SVM classifier initially and later it is optimized by the genetic algorithm using an ensemble technique. …”
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Harmonic Distortion Prediction Model of a Grid -Connected Photovoltaic Using Grey Wolf Optimizer - Least Square Support Vector Machine by Yasin Z.M., Ashida Salim N., Ab Aziz N.F.

Priority and dynamic quantum time algorithms for central processing unit scheduling by Mohammed, Maysoon A.

“…The proposed algorithms (Priority Dynamic Quantum Time and Multi Priority Dynamic Quantum Time Algorithms) are implemented using JAVA programming language and validated using Key Performance Indicators equations. …”
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A hybrid chromaticity-morphological machine learning model to overcome the limit of detecting newcastle disease in experimentally infected chicken within 36 h by Bakar, Mohd Anif A.A., Ker, Pin Jern, Tang, Shirley G.H., Arman Shah, Fatin Nursyaza, Mahlia, T. M.Indra, Baharuddin, Mohd Zafri, Omar, Abdul Rahman

“…Based on the HCMML models result, SVM with Polynomial kernel achieved a test accuracy of 82·39 % with 79·00 % validation accuracy at 36 h post-infection after feature optimization and > 95·00 % test accuracy after 96 h post-infection. …”
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Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…The features were tested with Support Vector Machine (SVM) and Extreme Learning Machine (ELM). This work improved due to the SI feature. …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”