Search Results - (( parallel optimisation system algorithm ) OR ( parameter visualization learning algorithm ))

Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

“…It describes a new scheduling approach, which is a combination of an updated conservative backfilling approach further optimised by the raccoon optimisation algorithm. This algorithm also proposes a technique of selection that combines job waiting and response time optimisation with user fairness. …”
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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

“…A number of benchmark function processes were conducted to assess the performance of proposed FOA (Fly Optimisation Algorithm).…”
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Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset by Ngahzaifa, Ab. Ghani, Zuriani, Mustaffa, Zafril Rizal, M Azmi

“…In using most of the machine learning algorithms including ANFIS, to obtain the best model, the common and normal approach is always by comparing models of different parameter settings based on the goodness-offit statistical measures. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking by Ong, Chor Keat

“…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

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Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing by Jaber, Aws Naser, Mohamad Fadli, Zolkipli, Shakir, Hasan Awni

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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 applied a deep extreme learning machine approach to predict the user parameters. …”
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Spectral analysis of discrete fourier transform (DFT) using Matlab by Wong Shen Yuong

“…In this project, signal is analyzed by applying Discrete Fourier Transform (DFT), specifically Fast Fourier Transform (FFT) algorithm in MATLAB. In the spectral analysis, the parameters are identified for signal analysis and the effect of varying the DFT parameters is studied. …”

Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

“…The visual analysis of foods on social media by using food recognition algorithm provides valuable insight from the health, cultural and marketing. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Therefore, the core classifier in the hyper-heuristic approach of Intrusion Detection System (IDS) is developed to the parallel structure NN. …”
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Vehicle Detection in Deep Learning by Teoh, Per Nian

“…The objective of this project is vehicle detection with deep learning, so, vehicles data set from highway, urban road and housing area had been collected and applied to the deep learning and computer vision algorithms. …”
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Five-level single source voltage converter controlled using selective harmonic elimination by Shanono, Ibrahim Haruna, Nor Rul Hasma, Abdullah, Aisha, Muhammad

“…The generated non-linear transcendental equations are solved using an optimised Genetic algorithms to find the switching angles. …”
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Exploration of COVID‑19 data in Malaysia through mapper graph by Carey Ling, Yu Fan, Piau, Phang, Liew, Siaw Hong, Vivek Jason, Jayaraj, Benchawan, Wiwatanapataphee

“…A support vector-based feature selection and a heuristic approach for fine-tuning parameters internally within the algorithm are conducted. …”
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Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

“…The visual analysis of foods on social media by using food recognition algorithm provides valuable insight from the health, cultural and marketing. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

“…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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