Search Results - (( using vector ((bat algorithm) OR (max algorithm)) ) OR ( java implication based algorithm ))

A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

“…Hence, to enhance the search ability of Cuckoo Search, it is integrated with Bat algorithm that offers a balanced search between global and local. …”
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DISSERTATION TITLE: AN OPTIMIZED SUPPORT VECTOR REGRESSION USING EVOLVED BAT ALGORITHM FOR HANDLING MISSING VALUES IN DATASETS

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A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

The Integration of Nature-Inspired Algorithms with Least Square Support Vector Regression Models: Application to Modeling River Dissolved Oxygen Concentration by Yaseen, Zaher, Ehteram, Mohammad, Sharafati, Ahmad, Shahid, Shamsuddin, Al-Ansari, Nadhir, El-Shafie, Ahmed

“…The current study investigates an improved version of Least Square Support Vector Machines integrated with a Bat Algorithm (LSSVM-BA) for modeling the dissolved oxygen (DO) concentration in rivers. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

“…However, they have their useful lives and will degrade over time. This issue prompts to be solved using predictive analytics to predict the Remaining Useful Life (RUL) of equipment. …”
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Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm by Mohamadi S., Sammen S.S., Panahi F., Ehteram M., Kisi O., Mosavi A., Ahmed A.N., El-Shafie A., Al-Ansari N.

MBIST implementation and evaluation in FPGA based on low-complexity March algorithms by Jidin, Aiman Zakwan, Mispan, Mohd Syafiq, Hussin, Razaidi, Weng, Fook Lee

“…They were implemented in the Intel Max 10 DE10-Lite FPGA Development Board. A test generator was built in FPGA, as an alternative to the external tester, to provide test vectors required in initiating the test on the memory model using the implemented MBIST. …”
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Development of colorization of grayscale images using CNN-SVM by Abualola, Abdallah, Gunawan, Teddy Surya, Kartiwi, Mira, Ambikairajah, Eliathamby, Habaebi, Mohamed Hadi

“…A convolutional neural network (CNN) was designed with several layers of convolutional and max pooling. Support Vector Machine (SVM) regression was used at the final stage. …”
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ANALYSIS OF BIOSENSOR PHYSIOLOGICAL SIGNALS FOR ASSESSMENT OF NEUROLOGICAL STATUS by QIAN XIN, SOONG

“…All the data signals of the 20 subjects will then be processed with features extraction method using mean, maximum (Max), minimum (Min), mean absolute deviation (MAD), Standard deviation (STD), interquartile range (IQR) and summation (Sum). …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Predicting Chlorophyll Intensity Of Various Plants Using Improved Convolutional Neural Network by Michelle, Nashrin Bawai

“…The proposed model consists of Hybrid CNN as a feature extractor and support vector regression (SVR) network as a predictor. Hybrid CNN was designed by modifying the architectures of AlexNet and PNet using MATLAB R2023a. …”
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Power amplifier memory polynomial predistorter for long term evolution application by Mazidi, Hossein

“…An open loop test bench is set up by using ZVE-8G+ power amplifier and Agilent equipment such as Agilent vector signal generator (VSG)EXG-D series and Agilent vector signal analyzer (VSA) PXI series in order to generate LTE down-link signal with 5 MHz bandwidth. …”
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CNN architectures for road surface wetness classification from acoustic signals by Bahrami, Siavash, Doraisamy, Shyamala, Azman, Azreen, Nasharuddin, Nurul Amelina, Yue, Shigang

“…Two CNN architectures with differing layouts for its dropout layers and max-pooling layers have been investigated. The positions and the number of the max-pooling layers were varied. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Automated diagnosis of diabetes using entropies and diabetic index by Acharya, U.R., Fujita, H., Bhat, S., Koh, J.E.W., Adam, M., Ghista, D.N., Sudarshan, V.K., Chua, K.P., Chua, K.C., Molinari, F., Ng, E.Y.K., Tan, R.S.

“…These redundant features are eliminated by using six feature selection algorithms: Student's t-test, Receiver Operating Characteristic Curve (ROC), Wilcoxon signed-rank test, Bhattacharyya distance, Information entropy and Fuzzy Max-Relevance and Min-Redundancy (MRMR). …”
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