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Autonomous path planning robot using geographical information by Ismail Ishaq Ibrahim

“…After the simulation using Matlab, the algorithm will then be implemented in the robot using basic stamp to run the mobile robot. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Dynamic path planning algorithm in mobile robot navigation by Yun, S.C., Parasuraman, S., Ganapathy, V.

“…MATLAB simulation is developed to verify and validate the algorithm before they are real time implemented on Team AmigoBotTM robot. …”
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A machine learning approach to tourism recommendations system by Chia, An

“…This project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. …”
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Development of a genetic algorithm controller for cartesian robot by Ong, Joo Hun

“…The electrical design involves wiring of control components such as the stepper motor controller, input and output devices as well as the power supply and the safety devices. Finally, the developed algorithm will been tested and implemented into in this Cartesian robot system.…”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…This algorithm has been tested and implemented successfully via a dual beam optical scanning system.…”
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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system by Balla, Asaad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Mubarak, Sinil

“…In this paper, we have examined and presented the most recent research on developing robust IDSs using Deep Learning (DL) algorithms, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Stacked Autoencoders (SAE), and Deep Belief Networks (DBN). …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam by Sarmad Dashti Latif, Mr.

Development Of Construction Noise Prediction Method Using Deep Learning Model by Siew, Jun Teng

“…A simple prediction chart method was developed on top of a stochastic algorithm called Monte Carlo simulation by complying with the standard BS 5228 for the noise prediction in the environmental impact assessment during the planning stage of a construction project. …”
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Intelligent Evolutionary Controller for Flexible Robotic Arm by Annisa, Jamali, Intan Z., Mat Darus

“…The developed evolutionary algorithms have been implemented and experimentally verified using robotic arm manipulator experimental rig. …”
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Loss minimization in load flow simulation in power system by Mohamad Firdaus, Mat Hussin

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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…Thus, through the implementation of machine learning, the researcher can analyse the proper and acceptable algorithms that can be used in heritage property price prediction which also are recommended for other researchers. …”
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Prioritisation assessment and robust predictive model for a comprehensive medical equipment maintenance using machine learning techniques / Aizat Hilmi Zamzam by Aizat Hilmi, Zamzam

“…The datasets are established according to nineteen features and criteria for this study. The development of predictive models for objectives 1 and 2 of this study involves the application of seven supervised machine learning algorithms. …”
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Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…In the future, it is advisable to collect additional contextual information, such as a compilation of public holidays and promotions, implement realtime modifications, evaluate more advanced algorithms and enhance staff training and data literacy. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.] by Razali, Mohd Norhisham, Ibrahim, Norizuandi, Hanapi, Rozita, Mohd Zamri, Norfarahzila, Abdul Manaf, Syaifulnizam

“…To address these challenges, we developed a predictive model using machine learning techniques to determine employee productivity within organizations. …”
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Diabetes risk prediction system and data visualization / Azizah Mohamad Imran and Hawa Mohd Ekhsan by Mohamad Imran, Azizah, Mohd Ekhsan, Hawa

“…To determine Diabetes, the prediction model used and compared different machine learning algorithms such as Logistic Regression (LR) and Support Vector Machine (SVM). …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

“…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Decision Support Tools: Machine Learning Application in Smart Planner by Baharom, M.A.A., Rahman, M.S.A., Sabudin, A.R., Nor, M.F.M.

“…Immaculate Project Planning and Execution (PPE) is capital to edge over competitors, decrease costs and honour delivery dates.Project Management Information System (PMIS) is necessary towards an improved and efficient quality of any project.Machine Learning (ML) Algorithms enabled learned the date of experience to develop insights into various associations between data and outcomes.A defined set of rules prescribed by the analysts makes the probability of the fault possible.In this paper, Regression Model compute across all viable sectors expending the tool for Downstream Business and other Facilities Upstream, including Resource Estimation Schedule Generation.Extending structured information into a reliable database allows super users to define the data structures and completely configurable the settingâ��s dynamics.The model used to decrease the approximation error and measure the closest possible outcome.This subset of artificial intelligence has tremendous potential in improving schedule generation configuration to develop Project Planning timely and financially smartly.This paper aims to share standard protocols and methods applied in ML-aided as a tool in PPE decision making.Additionally, the abundant used data resources devoted to implementing ML are outlined.Finally, ML success as a Decision Support tool in project management by having a Smart Planner in supporting project recommendation accelerates the decision process, increases stakeholder confidence, and minimizes uncertainty; results are reviewed and analyzed where gaps and potential improvement for future projects are being noted and highlighted. …”
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Learning representations of network traffic using deep neural networks for network anomaly detection: A perspective towards oil and gas it infrastructures by Naseer, S., Ali, R.F., Dominic, P.D.D., Saleem, Y.

“…In this study we propose, implement and evaluate use of Deep learning to learn effective Network data representations from raw network traffic to develop data driven anomaly detection systems. …”
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