Search Results - (( java implementation path algorithm ) OR ( using sector learning algorithm ))
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1
Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Thesis -
2
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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3
Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Article -
4
Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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5
DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Final Year Project -
6
Integrating finance dictionary in lexicon-based approach with machine learning algorithm to analyse the impact of OPEC news sentiment on financial market / Wu Ling
Published 2020“…The labelled sentences are then used to train the supervised machine learning classifiers. …”
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7
Diabetes prediction using machine learning / Muhammad Adib Mohd Nazri and Mahfudzah Othman
Published 2023“…Two types of machine learning, supervised and unsupervised, are used to assist patients and the medical sector. …”
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Book Section -
8
Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…When it comes to financial analysis, there are numerous risk-related concerns to contend with today (FI). In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
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9
An intelligent risk management framework for monitoring vehicular engine health
Published 2022“…We used machine learning and deep learning algorithms to assess the effectiveness of the risk management system’s decision model. …”
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10
Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023
Published 2024“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. …”
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Early prediction of acute kidney injury using machine learning algorithms
Published 2018“…The application of machine learning algorithms in the medical sector is gaining increased attention in the last few decades. …”
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Proceeding Paper -
12
Genetic programming based machine learning in classifying public-private partnerships investor intention / Ahmad Amin ... [et al.]
Published 2023“…The PPP data was analyzed in this study using two machine learning approaches, Genetic Programming and conventional machine learning, with testing results showing that all machine learning algorithms from both approaches achieved high accuracy rates of over 80%, with the Genetic Programming machine learning outperformed the conventional approach. …”
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13
Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting
Published 2021“…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
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Thesis -
14
Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Complex event pattern detection has become an emerging research area in various monitoring applications. For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Monograph -
15
Machine learning modeling for radiofrequency electromagnetic fields (RF-EMF) signals from mmWave 5G signals
Published 2023“…Additionally, the ICNIRP standard was used and compared with the results and validation values of the algorithms.…”
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16
The impact of news sentiment on the stock market fluctuation : the case of selected energy sector
Published 2021“…We developed a financial news sentiment classifier by combining machine learning algorithms and lexicon-based labelling methods. …”
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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
Published 2021“…Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms which are one of the challenging issues in the agricultural sector. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. Therefore, the proposed fuzzy model is a useful aid in the decision-making process, specifically in the healthcare sector.…”
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19
Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer
Published 2024“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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20
A review of deep learning and machine learning techniques for hydrological inflow forecasting
Published 2024“…Conventional machine learning models have been widely used for reservoir inflow and rainfall prediction. …”
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