Applications of Soft Computing in Time Series Forecasting: by Pritpal Singh

By Pritpal Singh

This ebook reviews on an in-depth research of fuzzy time sequence (FTS) modeling. It experiences and summarizes earlier examine paintings in FTS modeling and in addition offers a quick advent to different soft-computing options, reminiscent of synthetic neural networks (ANNs), tough units (RS) and evolutionary computing (EC), concentrating on how those ideas may be built-in into varied levels of the FTS modeling technique. particularly, the booklet describes novel equipment due to the hybridization of FTS modeling methods with neural networks and particle swarm optimization. It additionally demonstrates how a brand new ANN-based version should be effectively utilized within the context of predicting Indian summer time monsoon rainfall. due to its easy-to-read variety and the transparent causes of the versions, the e-book can be utilized as a concise but complete reference consultant to fuzzy time sequence modeling, and should be useful not just for graduate scholars, but additionally for researchers and execs operating for educational, company and executive organizations.

Show description

Read or Download Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques PDF

Best computer simulation books

Digital systems design with VHDL and synthesis

Ok. C. Chang offers an built-in method of electronic layout rules, procedures, and implementations to assist the reader layout more and more advanced structures inside of shorter layout cycles. Chang introduces electronic layout options, VHDL coding, VHDL simulation, synthesis instructions, and methods jointly.

The LabVIEW Style Book (National Instruments Virtual Instrumentation Series)

&>   Drawing at the reports of a world-class LabVIEW improvement association, The LabVIEW sort booklet is the definitive consultant to top practices in LabVIEW improvement. prime LabVIEW improvement supervisor Peter A. Blume offers useful directions or “rules” for optimizing each side of your functions: ease of use, potency, clarity, simplicity, functionality, maintainability, and robustness.

Robot Cognition and Navigation: An Experiment with Mobile Robots (Cognitive Technologies)

This publication provides the concept that of cognition in a transparent, lucid and hugely accomplished kind. It offers an in-depth research of mathematical types and algorithms, and demonstrates their software with genuine existence experiments.

Innovating with Concept Mapping: 7th International Conference on Concept Mapping, CMC 2016, Tallinn, Estonia, September 5-9, 2016, Proceedings

This ebook constitutes the refereed complaints of the seventh overseas convention on idea Mapping, CMC 2016, held in Tallinn, Estonia, in September 2016. The 25 revised complete papers awarded have been conscientiously reviewed and chosen from a hundred thirty five submissions. The papers tackle matters akin to facilitation of studying; eliciting, taking pictures, archiving, and utilizing “expert” wisdom; making plans guideline; evaluate of “deep” understandings; learn making plans; collaborative wisdom modeling; construction of “knowledge portfolios”; curriculum layout; eLearning, and administrative and strategic making plans and tracking.

Extra info for Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques

Sample text

The set of all objects which can be decisively classified neither as members of X nor as members of non-X with respect to R is called the boundary region of a set X with respect to R, and denoted by RS B . 4) Based on the notions shown in Fig. 4 (Crisp set). A set X is called crisp (exact) with respect to R if and only if the boundary region of X is empty. 4 Hybridize Modeling Approach for FTS 27 Fig. 5 (RS). A set X is called rough (inexact) with respect to R if and only if the boundary region of X is nonempty.

2007, 2008) presented new methods for temperature and the TAIFEX forecasting based on two-factors high-orders FLRs. (b) For finding best intervals using PSO: Recently, many researchers8 show that appropriate selection of intervals also increases the forecasting accuracy of the model. 9 They signify that PSO algorithm is more efficient and powerful than GA as applied by the researcher (Chen and Chung 2006b) in selection of proper intervals. 8 References 9 References are: (Huang et al. 2011a, b; Kuo et al.

2011a, b; Kuo et al. 2009, 2010). 30 2 Fuzzy Time Series Modeling Approaches: A Review Algorithm 2 Type-2 FTS Forecasting Model Step 1: Select Type-1 and Type-2 observations. Step 2: Determine the universe of discourse of time series data set and partition it into different/equal lengths of intervals. Step 3: Define linguistic terms for each of the interval. Step 4: Fuzzify the time series data set of Type-1 and Type-2 observations. 7. 8. Step 7: Establish the relationships between FLRGs of both Type-1 and Type-2 observations, and map-out them to their corresponding day.

Download PDF sample

Rated 4.60 of 5 – based on 36 votes