Search Results - (( java implementation path algorithm ) OR ( risk prediction function algorithm ))

Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

“…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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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…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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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

“…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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Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

“…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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Landslide risk zoning using support vector machine algorithm by Ghiasi V., Pauzi N.I.M., Karimi S., Yousefi M.

Subjects: “…kernel functions…”

Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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A novel approach based on machine learning and public engagement to predict water-scarcity risk in urban areas by Hanoon, Sadeq Khaleefah, Abdullah, Ahmad Fikri, M. Shafri, Helmi Z., Wayayok, Aimrun

“…The approach was used to detect (WSR) in two ways, namely, prediction using ML models directly and using the weighted linear combination (WLC) function in GIS. …”
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Early prediction of acute kidney injury using machine learning algorithms by Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Dzaharudin, Fatimah, Mat Ralib, Azrina, Md Nor, Norzaliza, Yahya, Norzariyah

“…Thus, the main aim of this manuscript is to compare the performance of well-known machine learning (ML) algorithms to a problem in the domain of medical diagnosis and analyze their efficiency in predicting the results. …”
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Modelling of default risk for home credit data using machine learning approach by Tan, Darren Tik Lun

“…This indicated the practicality of the LightGBM algorithm for the mortgage loan risk and prediction analysis of delinquent profiles for financial institutions.…”
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Development of noise induced hearing loss prediction model using artificial neural network / Siti Fairus Mohd Zain by Mohd Zain, Siti Fairus

“…The 24 input layers encompassed 12 risk factors and 12 audiogram variables. It also embedded with 10 hidden layers in the prediction models using Levenberg-Marquardt algorithm as a transfer function from input vectors to the five binary outputs. …”
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Prediction of COVID-19 patient using supervised machine learning algorithm by M., Buvana, K., Muthumayil

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SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

“…The cubic kernel function was found suitable for training SVMs. Besides, a feed-forward artificial neural network with the backpropagation algorithm and a polynomial surface fit model have also been developed to predict the MIT. …”
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A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

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Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

“…Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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Formulation Of Fitness Function To Predict Ph Value Of Adjacent Block Via Ph Value, Water Flow Speed And Direction by Nurul Najihah, Mohd Radzi

“…Collect large set of data which comprises of five location, four of the locations pH are used to determine the fifth location pH. To predict the lake water quality, we are using fitness function that has been formulate using Multi-Layer Neural Network by Genetic Algorithm (MLNN-GA) and compare the results in terms of accuracy of prediction. …”
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Small Farmers' Decisions: Utility Versus Profit Maximization by Mohayidin, Mohd. Ghazali

“…Farmer's risk attitudes are modelled using the Cobb-Douglas, transcendental, negative exponential, and conjoint measurement utility functions. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

“…Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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Evolutionary automated radial basis function neural network for multiphase flowing bottom-hole pressure prediction by Campos, Deivid, Wayo, Dennis Delali Kwesi, De Santis, Rodrigo Barbosa, Martyushev, Dmitriy A., Yaseen, Zaher Mundher, Duru, Ugochukwu Ilozurike, Saporetti, Camila M., Goliatt, Leonardo

“…This research presents a data-driven hybrid approach that uses a Radial Basis Function Neural Network and a Particle Swarm Optimization algorithm to construct an automated hybrid machine learning model. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

“…Plots of survival distribution function against failure time are used to examine the predicted survival patterns for the two types of failures. …”
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Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)... by Pradhan, Biswajeet, Mohammad Zare, Pourghasemi, Hamid Reza, Vafakhah, Mahdi

“…Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. …”
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