Search Results - (( java segmentation using algorithm ) OR ( knowledge forecasting using algorithm ))
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Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Thesis -
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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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Monograph -
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Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…The network structures are normally selected on the basis of the developer's prior knowledge or hit and trial approach is used for this purpose. …”
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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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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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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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Intelligent inventory forecasting system / Fadzlinor Mustapa
Published 2006“…This project is about producing a prototype of forecasting system by using artificial neural methods that will forecast stock level in the inventory. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…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. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…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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Research Reports -
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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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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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Rule extraction from multi-layer perceptron neural network using decision tree for currency exchange rates forecasting
Published 2015“…Neural network can be used in acquiring hidden knowledge in datasets. However, knowledge acquired by neural network was presented in its topology, the weights on the connections and by the activation functions of the hidden and output nodes. …”
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