Search Results - (( developing effective rainfall algorithm ) OR ( java visualization learning algorithm ))
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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Monograph -
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Conference or Workshop Item -
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Rainfall time series modeling for a mountainous region in West Iran
Published 2010“…A feedforward Artificial Neural Network (ANN) rainfall model and a Seasonal Autoregressive Integrated Moving Average (SARIMA) rainfall model were developed to investigate their potentials in forecasting rainfall. …”
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Thesis -
4
Daily Rainfall Forecasting Using Meteorology Data with Long Short-Term Memory (LSTM) Network
Published 2022“…For time series data forecasting, the Long Short-Term Memory (LSTM) network is shown to be superior as compared to other machine learning algorithms. Therefore, in this research work, a LSTM network is developed to predict daily average rainfall values using meteorological data obtained from the Malaysian Meteorological Department for Kuching, Sarawak, Malaysia. …”
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Article -
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…The increase in temperature could influence time and magnitude of rainfall by shifting dry and wet seasons. Moreover, the output results indicate a decrease in monthly rainfall. …”
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Thesis -
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. …”
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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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Investigation of Multimodel Ensemble Performance Using Machine Learning Method for Operational Dam Safety
Published 2023“…Hence, consideration of the development of more flexible inflow forecasting systems is needed. …”
Book Chapter -
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Rainfall modeling using two different neural networks improved by metaheuristic algorithms
Published 2024“…Rainfall is crucial for the development and management of water resources. …”
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Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
Published 2024“…This study aims to investigate the requirements of utilizing the Artificial Neural Network algorithm for prediction of dengue outbreak. The objective is to develop Dengue Outbreak Prediction System using Artificial Neural Network algorithm and evaluate its performance. …”
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Thesis -
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Performance Measurement on Deep Spiking Neural Network (DSNN) Algorithm in Flood Prediction Environment
Published 2023“…Rainfall data from 30 years (1989-2019) was collected from DID to evaluate the effectiveness of the DSNN algorithm compared to traditional and shallow neural networks algorithms. …”
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Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables
Published 2025“…However, current models often rely on coarse regional data and fail to account for microclimatic variations, limiting their predictive accuracy in dengue hotspots. This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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Optimal allocation and sizing of capacitor bank and distributed generation using particle swarm optimization
Published 2021“…The research work presented in this thesis had investigated the effect of two additional weather parameters, namely wind speed and rainfall, in addition to the temperature and relative humidity using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in predicting the values of load demands. …”
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Study of climate change effects on rain height for satellite microwave links
Published 2024“…Then, a simple AI predictive model for rain height is being developed by using Artificial Neural Network (ANN) algorithms with Python programming language. …”
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Final Year Project / Dissertation / Thesis -
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Forecasting model for the change in stage of reservoir water level
Published 2016“…During floods, early reservoir water release is one of the actions taken by the reservoir operator to accommodate incoming heavy rainfall. Late water release might give negative effect to the reservoir structure and cause flood at downstream area. …”
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Advanced data mining techniques for landslide susceptibility mapping
Published 2021“…These predicted datasets were used to develop the Landslides Susceptibility Models. A comparative assessment between the two classifiers against the famous traditional learning algorithm, the Support vector machines (SVM), was conducted. …”
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Article -
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Flood prediction model for Kuala Terengganu area using predictive analytics
Published 2025“…Three classification algorithms were tested: Decision Tree, Naive Bayes, and Random Forest. …”
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Student Project -
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Rain models for the prediction of fade duration at millimeter wavelengths
Published 2006“…The planning of radio communications system requires an estimate of the average annual outage due to fading, which at millimeter wavelengths, is generally dominated by the effects of rain attenuation. Current ITU-R recommendations provide algorithm for estimating the exceedance static of rain-induced attenuation on terrestrial links. …”
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Thesis
