Search Results - (( java implication based algorithm ) OR ( based formation learning algorithm ))

Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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Multi-Agent Reinforcement Learning For Swarm Robots Formation by Bujang, Christina

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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

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Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

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Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles by Yaghoobi, Yousef, Bahiki, Muhammad Rijaluddin, Syaril Azrad

“…In addition, several different techniques and approaches for developing the algorithm is discussed as well. As per system requirements and conducted study, the algorithm that is developed for this Vision System is based on Tracking and On-Line Machine Learning approach. …”
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Video content adaptation based on user preferences and network bandwidth / Badariyah Bakhtiar by Bakhtiar, Badariyah

“…Based on the experiment results, it is proved that the video content adaptation under e-learning environment can be achieved by the algorithms effectively.…”
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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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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…A comparison of deep learning convolutional neural network and artificial neural network algorithms was also performed, with findings revealing that convoluted input formation was less stochastic than feedforward formation, particularly for a more complicated series and vice versa, due to its capacity to attract features. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

“…To address this challenge, the paper proposed XGB5hmC, a machine learning algorithm based on a robust gradient boosting algorithm (XGBoost), with different residue based formulation methods to identify 5hmC samples. …”

Comparison between pixel-based and object based classifications using radar satellite image in extracting massive flood extent at northern region of Peninsular Malaysia by Abd Manaf, Syaifulnizam, Mustapha, Norwati, Mohd Shafri, Helmi Zulhaidi, Sulaiman, Md. Nasir, Husin, Nor Azura

“…TerraSAR-X image was used to map the flood extent of the study area. In object-based approach, there were three simple machine learning algorithms such as PP, MD, MH together with NN performed with high accuracy while in pixel based approach, NN was the highest accuracy of all machine learning algorithms. …”
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Comparison between pixel-based and object-based classifications using radar satellite image in extracting massive flood extent at northern region of Peninsular Malaysia by Abd Manaf, Syaifulnizam, Mustapha, Norwati, Mohd Shafri, Helmi Zulhaidi, Sulaiman, Md Nasir, Husin, Nor Azura

“…TerraSAR-X image was used to map the flood extent of the study area. In object-based approach, there were three simple machine learning algorithms such as PP, MD, MH together with NN performed with high accuracy while in pixel based approach, NN was the highest accuracy of all machine learning algorithms. …”
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MFA-OSELM Algorithm For Wifi-Based Indoor Positioning System by AL-Khaleefa, Ahmed Salih, Mohd Riduan, Ahmad, Awang Md Isa, Azmi, AL-Saffar, Ahmed, Mohd Esa, Mona Riza, Malik, Reza Firsandaya

“…Facilitating the use of WiFi for this purpose requires fingerprint formation and the implementation of a learning algorithm with the aim of using the fingerprint to determine locations. …”
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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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Machine Learning in Asphaltenes Mitigation by Qasim, A., Lal, B.

“…For asphaltenes predic­tion, preceding studies have used thermodynamic solubility technique, colloidal based models. Currently researchers have focused on machine learning techniques to predict the conditions of asphaltenes formation. …”
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MFA-OSELM algorithm for WiFi-based indoor positioning system by Al-Khaleefa, Ahmed Salih, Mohd Riduan, Ahmad, Azmi Awang, Md Isa, Al-Saffar, Ahmed Ali Mohammed, Mona Riza, Mohd Esa, Reza Firsandaya, Malik

“…Facilitating the use of WiFi for this purpose requires fingerprint formation and the implementation of a learning algorithm with the aim of using the fingerprint to determine locations. …”
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Hybrid BLEU Algorithm For Structured Exam Management System by Zulhana, Zulkifle

“…The lectures believed that this system can be upgraded according to the administration format. As a conclusion, this system has effectively aid the teaching and learning process at Community College.…”
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Modeling total quality management in higher education with case-based reasoning by Jani H.M.

“…This paper emphasizes on the mastery learning approach, which is in line with TQM. The learning process contains the following steps: Plan, teach (Do), Check (formative evaluation), revised teaching (Act), and Test (summative evaluation). …”

Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

“…This study investigated the feasibility and effectiveness of image-based techniques using advanced deep learning algorithms to quantify desiccation cracks in expansive soils. …”
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Machine-Learning Based QoE Prediction For Dash Video Streaming by Tan, Jun Yuan

“…However, conventional models are established based on machine learning techniques, which are unable to extract high-level features from low-level raw inputs via a hierarchical learning process. …”
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