[PDF] Top 20 A Proposed Model For Forecasting Stock Markets Based On Clustering Algorithm And Fuzzy Time Series
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A Proposed Model For Forecasting Stock Markets Based On Clustering Algorithm And Fuzzy Time Series
... the proposed method to forecast TAIFEX index with the whole historical data [8], from 8/3/1998 to 9/30/1998 are used to perform comparative study in the training ...the forecasting effectiveness of the ... See full document
6
A Hybrid Forecasting Model Based On Automatic Clustering Algorithm And Fuzzy Time Series
... hybrid model for forecasting the enrolments of University of Alabama based on Automatic clustering technique and ...automatic clustering technique to classify the collected data into ... See full document
7
A Forecasting Model Based On Combining Automatic Clustering Technique And Fuzzy Time Series
... Abstract—Most fuzzy forecasting methods are based on modelling fuzzy logical relationships according to the past ...hybrid forecasting model based on two computational ... See full document
6
Design of a Fuzzy Time Series Forecasting Model for Hydro Power Generation
... al.,(2010) proposed Traditional Time Series Method (ARIMA model and Vector ARMA model) and Fuzzy Time Series Method (Two-factor model, Heuristic ... See full document
5
Forecasting Model For Enrolment Combining Weighted Fuzzy Time Series And Fourier Series Transform
... [2] proposed the time-invariant FTS and the time-variant FTS model which use the max–min operations to forecast the enrolments of the University of ...[3] proposed the first-order FTS ... See full document
6
Enrollments Forecasting Based On Aggregated K Means Clustering and Fuzzy Time Series
... time series used the static length of intervals, ...for forecasting enrolments based on Fuzzy Time Series and K-Mean ...the proposed model, the empirical ... See full document
7
Modified weighted for enrollment forecasting based on fuzzy time series
... study proposed the modified weighted for fuzzy time series ...weighted fuzzy time series models for Taiwan stock index (TAIEX) forecasting where it was ... See full document
12
Article Forecasting Based on High-Order Fuzzy-Fluctuation Trends and Particle Swarm Optimization Machine Learning Jingyuan Jia 1, Aiwu Zhao 1, * and Shuang Guan 2
... existing fuzzy forecasting models partition historical training time series into fuzzy time series and build fuzzy-trend logical relationship groups to generate ... See full document
13
Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm
... [26] proposed a hybrid ANFIS model for forecasting monthly electricity demand in Iran and yielded good results compared to time series model, genetic algorithm and neural ... See full document
31
A GARCH based method for clustering of financial time series: International stock markets evidence
... for clustering analysis of …nancial time ...the stock return volatilities. The proposed method uses the volatility behavior of the time series and solves the problem of di¤erent ... See full document
13
A Forecasting Model Based On K-means Clustering And Time-invariant Fuzzy Relationship Groups
... the fuzzy forecasting methods based on fuzzy time series used the static length of intervals, ...improved forecasting model is used to forecast the student ... See full document
7
A Segment Length And Weight Optimized Fuzzy Time Series For Cloud Load Prediction
... been proposed for cloud data center load ...WSVM algorithm exploits the wavelet transform in detecting the frequency related characteristics of workload, and non-linear regression capability of ...The ... See full document
9
Forecasting Outlier Occurrence in Stock Market Time Series Based on Wavelet Transform and Adaptive ELM Algorithm
... paper, forecasting models mostly have been used to forecast the stock market index value ...The proposed AD-ELM method is successfully used for market indexes of Tehran Over-the-Counter Market (OTC) ... See full document
7
A New Hybrid Fuzzy Time Series Forecasting Model Combined the Time -Variant Fuzzy Logical Relationship Groups with Particle Swam Optimization
... CC06a model [10], HPSO model [14], AFPSO model ...each model are presented in Table 9, where the proposed method shows better forecasting accuracy than CC06a model using ... See full document
15
Algorithms for Data-Driven Business Intelligence with Applications to Revenue Optimization and Financial Forecasting.
... the proposed model, we analyze data sets from four major world trading markets (DJI, DAX, NIKKEI and TAIEX) obtained from Yahoo Finance (https: // ...every stock market index, we work with ... See full document
120
Improved models in fuzzy time series for forecasting
... While forecasting the stock market was one of the main application in fuzzy time series researches, absence of any standard model to facilitate making a stock forecast ... See full document
32
ARIMA: An Applied Time Series Forecasting Model for the Bovespa Stock Index
... a model that adequately describes the causal rela- tionships which may exist in reality, leading to the understanding of the current processes thus, fostering under- standing of real ... See full document
10
Temporal Forecast Demand of Cloud Based Media Streaming Applications for Efficient Resource Allocation
... cloud based media streaming providers an issue pertaining to resource ...reservation based resource allocation needs to be improved for ...we proposed and implemented a time-series ... See full document
9
Design and Implementation of Modified Fuzzy based CPU Scheduling Algorithm
... logic based algorithms are getting more popularity now a day as Reza salami et ...scheduling algorithm for computational grids using NSGA II with fuzzy variance based crossover ...this ... See full document
6
A Review on Clustering Analysis based on Optimization Algorithm for Datamining
... of clustering. The clustering is one of the problem in data mining that always focus on many ...researchers. Clustering technique is one of the important unsupervised classification ...C-mean ... See full document
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