Search Results - (( knowledge forecasting based algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…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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Automated time series forecasting
Published 2011“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Market prices trend forecasting supported by Elliott Wave's theory
Published 2017“…The trend prediction is supported by application of recognized Elliot waves which was performed by custom developed algorithm based on available knowledge about the patterns. …”
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…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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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…Finally, future estimations of EEC in ASEAN-5 countries are projected up to 2030 by applying the rolling-based forecasting procedure on mathematical models derived from optimized GEP. …”
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8
SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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Type 2 Fuzzy Inference-Based Time Series Model
Published 2019“…Furthermore, the weighted subsethood-based algorithm was applied in developing fuzzy IF–THEN rules, where it was later used to perform forecasting. …”
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Forecasting Crude Palm Oil Prices Using Fuzzy Rule-Based Time Series Method
Published 2018“…Therefore, this research develops a new CPO price forecasting method using weighted subsethood-based algorithm in order to generate fuzzy rules of forecasting. …”
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Forecasting Crude Palm Oil Prices Using Fuzzy Rule-Based Time Series Method
Published 2018“…Therefore, this research develops a new CPO price forecasting method using weighted subsethood-based algorithm in order to generate fuzzy rules of forecasting. …”
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A web usage mining approach based on LCS algorithm in online predicting recommendation systems
Published 2008“…This huge amount of data can be a useful source of knowledge. Advanced mining processes are needed for this knowledge to be extracted, understood and used. …”
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Rule extraction from multi-layer perceptron neural network using decision tree for currency exchange rates forecasting
Published 2015“…The main process in extracting rules from MLP using decision tree for currency exchange rate forecasting can be divided into two stages. In the first stage, the MLP network was built based on the parameter that was defined in the previous chapter. …”
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A new classification model for online predicting users' future movements
Published 2008“…We can exploit Web Usage Mining for Knowledge extracting based on user behavior during the web navigation. …”
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Hybrid Genetic Algorithm based Fuzzy Inference System for Data Regression
Published 2023Conference Paper -
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…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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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Multi agent and artificial neural networks prediction framework development for stock investment strategy
Published 2016“…The ontology developed is not limited to just a knowledge base to store data in structured format but it plays an important role as an inference sources in the decision making of the buying and selling of stock by performing fundamental analysis. …”
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Multi-agent and artificial neural networks prediction framework development for stock investment strategy
Published 2016“…The ontology developed is not limited to just a knowledge base to store data in structured format but it plays an important role as an inference sources in the decision making of the buying and selling of stock by performing fundamental analysis. …”
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