Search Results - (( developing agent machine algorithm ) OR ( java application customization algorithm ))
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…Moreover, agent-based behavioral models of the nanomotors are developed using state machine diagrams of UML to illustrate the internal autonomous and intelligent decision-making processes of the nanomotors. …”
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A machine learning approach to tourism recommendations system
Published 2025“…This project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. …”
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Extreme Learning Machine neural networks for multi-agent system in power generation
Published 2023“…This particular approach was included in a Multi-Agent System (MAS). By hybrid those two approached, a novel extreme learning machine based multi-agent systems (ELM-MAS) for handling classification problems is presented in this paper. …”
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Deep reinforcement learning to multi-agent deep reinforcement learning
Published 2022“…In the third section, we look at the RL and important algorithms that exist in this area. In the fourth section, we study DRL and explain the reasons for which different algorithms have been developed in this regard. …”
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Development of appoinment scheduling agent using distributed constraint satisfaction (DisCS)
Published 2008“…The goal of this research is to develop appointment scheduling agent in reservation environment with implementation of Distributed Constraint Satisfaction (DisCS). …”
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Efficient and effective automated surveillance agents using kernel tricks
Published 2012“…In this paper we present three software-based agents built using kernel machines to perform automated, real-time intruder detection in surveillance systems. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
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Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI
Published 2024“…Additionally, the SVM algorithm was evaluated based on its performance across different DWI bvalues, aiming to optimize scanning time. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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Automate customer support handling E-Commerce enquiry using ChatGPT
Published 2024“…The project scope is the development of a comprehensive mechanism for context handling, an inconspicuous human takeover process, and the summarization of entire conversations between customers and automated customer support before handover to human agents. …”
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Final Year Project / Dissertation / Thesis -
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…Othman develop a predictive algorithm named R-HCSVM to predict protein local structure that works with following steps. …”
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization
Published 2022“…One of the two input features is P (bar) and the other is T (k). ADA-DT (Adaboost Algorithm Decision Tree), ADA-LR (Adaboost Algorithm-Linear Regresion), and ADA-GRNN (Generative Regression Neural Network) models showed MAE of 6.54 ˣ 10ˉ⁵, 4.66 10 ˉ⁵, and 8.35 10 ˉ⁵, respectively. …”
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Path planning methods for autonomous vehicles at intersections: A review
Published 2026“…Furthermore, the review highlights key challenges such as handling dynamic multi-agent environments, managing interactions with human-driven vehicles, and balancing computational efficiency with path optimality and discusses potential solutions through adaptive, real-time algorithms, cooperative planning, and predictive modelling. …”
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