Search Results - (( java implementation path algorithm ) OR ( knowledge forecasting learning 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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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

“…The proposed technique provides a pathway to determine the best ANN architecture, prior to the training and learning process of neural network. Multi-objective algorithm is proposed in this research which optimizes the ANN architecture that leads to enhancement in load forecast accuracy and reduction in the computational cost. …”
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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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Change vulnerability forecasting using deep learning algorithm for Southeast Asia by Amelia Ritahani, Ismail, Nur ‘Atikah, Mohd Ali, Junaida, Sulaiman

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Intelligent inventory forecasting system / Fadzlinor Mustapa by Mustapa, Fadzlinor

“…The general finding for this project is that with Back propagation algorithm, the suitable learning rate for forecasting prototype is 0.1 with architecture 7-11-1 that is seven nodes employed in the input layer, eleven nodes in the hidden layer and lastly one node employed in the output layer.…”
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Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

“…The forecasting of the stock markets' trends is one of the most frequently applied point of interests in machine learning (ML) industry from its beginning. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…The objective of this study is to suggest the potential classification model for talent forecasting throughout some experiments using SVM learning algorithm. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

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Improved prediction of daily pan evaporation using Bayesian Model Averaging and optimized Kernel Extreme Machine models in different climates by Ehteram M., Graf R., Ahmed A.N., El-Shafie A.

“…Bayesian networks; Climate models; Forecasting; Knowledge acquisition; Machine learning; Particle swarm optimization (PSO); Uncertainty analysis; Water resources; Wind; Bayesian model averaging; Daily pan evaporation; Gamma test; Kernel extreme learning machine model; Learning machines; Machine modelling; Optimization algorithms; Uncertainty; Water planning; Water resources management; Evaporation; algorithm; Bayesian analysis; evaporation; machine learning; numerical model; optimization; stochasticity; uncertainty analysis…”

An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery by Aziz A., Essam Y., Ahmed A.N., Huang Y.F., El-Shafie A.

Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development by Pande C.B., Egbueri J.C., Costache R., Sidek L.M., Wang Q., Alshehri F., Din N.M., Gautam V.K., Chandra Pal S.

“…The ensemble framework combines three powerful machine learning algorithms: XG-Boost, Bagging-XG-Boost, and AdaBoost, to enhance the accuracy and robustness of LST predictions. …”

Convolutional neural networks and deep belief networks for analysing imbalanced class issue in handwritten dataset by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

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Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis by Baashar Y., Alkawsi G., Alhussian H., Capretz L.F., Alwadain A., Alkahtani A.A., Almomani M.