Search Results - (( ais implementation level algorithm ) OR ( java application learning algorithm ))

Application of minimax algorithm in dots and boxes game by Tan, Ah Hwa

“…The methodology involved implementing the Minimax algorithm as the primary decision-making engine for the AI. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

“…The approach is realised within SISO and SIMO AVC structures using RCGA, PSO and AIS algorithms. These are implemented on the flexible plate structure with various disturbance signals. …”
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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

“…After that, a bi-objectives algorithm is tested for comparing purposes and this contributed for the next two sub-objectives that is 3) to test the feasibility for implementing the PDE hybrid FFNN. 4) to compare single objective and multi-objective optimization algorithms performances. …”
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Improved coupled tank liquid levels system based on hybrid genetic-immune adaptive tuning of PI controller by S. M., Nawi, Abdalla, Ahmed N., Mohd Syakirin, Ramli

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Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

“…AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

“…AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana by Gerhana, Yana Aditia

“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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AI recommendation penetration testing tools for password attacks: random forest by Rozman, Nurulasyiqin, Saad, Shahadan

“…This project developed an AI-based recommendation system using the Random Forest algorithm to address the complexities of selecting appropriate penetration testing tools for password attacks. …”
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions by Gerhana, Yana Aditia

“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Alam, Mohammad Nur‑E, Soudagar, Manzoore Elahi Mohammad

“…In UW, ANN, Hybrid ANN, and ML models predict output parameters with accuracy levels ranging from 85 to 96%. Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. …”
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Potential of Metal Artifact Reduction (MAR) and Deep Learning-based Reconstruction (DLR) algorithms integration in CT Metal Artifact Correction: a review by Mohammed Musta, Njiti, Osman, Noor Diyana, Mansor, Mohd Syahir, Rabaiee, Nor Ain, Abdul Aziz, Mohd Zahri

“…Current DLR implementations like TrueFidelity and Advanced Intelligent Clear-IQ Engine (AiCE) demonstrate promising outcomes. …”
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A Study on Gradient Boosting Algorithms for Development of AI Monitoring and Prediction Systems by Aziz, N., Akhir, E.A.P., Aziz, I.A., Jaafar, J., Hasan, M.H., Abas, A.N.C.

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Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

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AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Nur‑E‑Alam, Mohammad, Soudagar, Manzoore Elahi Mohammad

“…In UW, ANN, Hybrid ANN, and ML models predict output parameters with accuracy levels ranging from 85 to 96%. Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. …”
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