Search Results - (( java implication tree algorithm ) OR ( grey relational data algorithm ))

Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model by Salleh, Roselina, Shamsuddin, Siti Mariyam

“…Accordingly, the aim of this research is to develop a new hybrid model by combining a linear and nonlinear model for forecasting time series data. The proposed model (GRANN_ARIMA) integrates nonlinear grey relational articial neural network (GRANN) and linear ARIMA model, combining new features such as multivariate time series data as well as grey relational analysis to select the appropriate inputs and hybridization succession. …”
Get full text
Get full text

Improvement of adaptive GAs and back propagation ANNs performance in condition diagnosis of multiple bearing system using grey relational analysis by Wulandhari, Lili A., Wibowo, Antoni, Desa, Mohammad I.

“…Condition diagnosis of multiple bearings system is one of the requirements in industry field, because bearings are used in many equipment and their failure can result in total breakdown.Conditions of bearings commonly are reflected by vibration signals data.In multiple bearing condition diagnosis, it will involve many types of vibration signals data; thus, consequently, it will involve many features extraction to obtain precise condition diagnosis.However, large number of features extraction will increase the complexity of the diagnosis system.Therefore, in this paper, we presented a diagnosis method which is hybridization of adaptive genetic algorithms (AGAs), back propagation neural networks (BPNNs), and grey relational analysis (GRA) to diagnose the condition of multiple bearings system.AGAs are used in the diagnosis algorithm to determine the best initial weights of BPNNs in order to improve the diagnosis accuracy.In addition, GRA is applied to determine and select the dominant features from the vibration signal data which will provide good diagnosis of multiple bearings system in less features extraction.The experiments results show that AGAs-BPNNs with GRA approaches can increase the accuracy of diagnosis in shorter processing time, compared with the AGAs-BPNNs without the GRA.…”
Get full text
Get full text

Improvement of adaptive GAs and Back propagation ANNs performance in condition diagnosis of multiple bearing system using grey relational analysis by Wulandhari, Lili A., Wibowo, Antoni, Desa, Mohammad I.

“…Conditions of bearings commonly are reflected by vibration signals data.In multiple bearing condition diagnosis, it will involve many types of vibration signals data; thus, consequently, it will involve many features extraction to obtain precise condition diagnosis.However, large number of features extraction will increase the complexity of the diagnosis system.Therefore, in this paper, we presented a diagnosis method which is hybridization of adaptive genetic algorithms (AGAs), back propagation neural networks (BPNNs), and grey relational analysis (GRA) to diagnose the condition of multiple bearings system. …”
Get full text
Get full text

Metaheuristic optimization of perovskite solar cell performance using Taguchi grey relational analysis with grey wolf optimizer by Salehuddin, Fauziyah, Mat Junos @ Yunus, Siti Aisah, Ahmad Jalaludin, Nabilah, Mohd Nazli, Nurul Farina, Arith, Faiz, Mohd Zain, Anis Suhaila, Mohamd Rafidi, Nur Ruzanna, Kaharudin, Khairil Ezwan

“…The metaheuristic approach sequentially employs the L27 orthogonal array (OA) Taguchi-based design of experiment (DoE), Grey Relational Analysis (GRA), Multiple Linear Regression (MLR) and Grey Wolf Optimizer (GWO). …”
Get full text
Get full text
Get full text

Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

“…In this study, the uncertainty and nonstationary characteristics of streamflow data has been treated using a set of coupled data pre-processing methods before being considered as input for an artificial neural network algorithm namely; rolling mechanism (RM) and grey models (GM). …”
Get full text
Get full text

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…In line with the No Free Lunch theorem which suggests that no single metaheuristic is the best for all optimization problems, the search for better algorithms is still a worthy endeavour. Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
Get full text
Get full text

A comprehensive evaluation of public hospitals in Malaysia using several grey relational analysis models / Muhammad Arif Ahmad Zaki, Nur Hanis Kaha Mohd Kaharuddin and Zureen Syazi... by Ahmad Zaki, Muhammad Arif, Mohd Kaharuddin, Nur Hanis Kaha, Zalman Zain, Zureen Syazira

Get full text
Get full text

Customer satisfaction evaluation of water quality using fuzzy conjoint and grey relational analysis method / Nur Hadirah Asmadi, Nur Azizah Mohd Arifin and Norfaradiana Mariani by Asmadi, Nur Hadirah, Mohd Arifin, Nur Azizah, Mariani, Norfaradiana

Get full text
Get full text

Integration of grey analysis with artificial neural network for classification of slope failure by Deris A.M., Solemon B., Omar R.C.

“…However, the prediction result of ANN can be improved by integrating the statistical analysis method, namely grey relational analysis (GRA), to the ANN model. …”

Time series forecasting of energy commodity using grey wolf optimizer by Yusof, Yuhanis, Mustaffa, Zuriani

“…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
Get full text
Get full text
Get full text

Metaheuristic Algorithms and Neural Networks in Hydrology

“…This book summarizes the latest research and developments related to the application of nature-inspired metaheuristic algorithms coupled with artificial neural networks (ANNs) in hydrology. …”
Get full text
Get full text
Get full text

Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer by Zuriani, Mustaffa, Yuhanis, Yusof

“…In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting. …”
Get full text
Get full text
Get full text

An application of barnacle mating optimizer in infectious disease prediction: a dengue outbreak cases by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Mohamad Farhan, Mohamad Mohsin, Yuhanis, Yusof, Ferda, Ernawan, Bariah, Yusob, Noorhuzaimi, Mohd Noor

“…In addition, meteorological data sets were also been employed as input. For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Mean Absolute Deviation (MAD) were employed to validate the performance of the identified algorithms which includes the comparison between BMO against Moth Flame Optimizer (MFO) and Grey Wolf Optimizer (GWO) algorithms. …”
Get full text
Get full text
Get full text

Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

“…Then, the TTA is developed before undergoing functionality tests by benchmarking with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA). …”
Get full text
Get full text

Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…This proposed algorithm also discerned linear and nonlinear subsystem variables within a continuous-time Hammerstein model utilizing input and output data. …”
Get full text
Get full text
Get full text
Get full text

Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

“…In addition, the MLLF algorithm reduces the maximum delay threshold by an average of 11% compared with other related algorithms. …”
Get full text
Get full text
Get full text

A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

“…However, the prediction result of ANN can be improved by integrating the statistical analysis method, namely grey relational analysis (GRA), to the ANN model. …”

Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…This study concluded that remote sensing approach combined with data mining approaches such as ANN algorithms have great potential in monitoring vast plantation areas in a rapid and inexpensive manner.…”
Get full text
Get full text
Get full text