標(biāo)題: Titlebook: Applications of Soft Computing in Time Series Forecasting; Simulation and Model Pritpal Singh Book 2016 Springer International Publishing S [打印本頁(yè)] 作者: Exacting 時(shí)間: 2025-3-21 18:04
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書(shū)目名稱(chēng)Applications of Soft Computing in Time Series Forecasting讀者反饋
書(shū)目名稱(chēng)Applications of Soft Computing in Time Series Forecasting讀者反饋學(xué)科排名
作者: habile 時(shí)間: 2025-3-21 20:56 作者: 手銬 時(shí)間: 2025-3-22 02:33
Book 2016 clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series?modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations...?.作者: Guaff豪情痛飲 時(shí)間: 2025-3-22 07:25 作者: neutralize 時(shí)間: 2025-3-22 11:12 作者: manifestation 時(shí)間: 2025-3-22 14:07 作者: 被告 時(shí)間: 2025-3-22 19:58
Book 2016 provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes nove作者: Gentry 時(shí)間: 2025-3-22 23:47 作者: 有幫助 時(shí)間: 2025-3-23 04:37
Studies in Fuzziness and Soft Computinghttp://image.papertrans.cn/a/image/159568.jpg作者: 嬰兒 時(shí)間: 2025-3-23 07:52 作者: 不近人情 時(shí)間: 2025-3-23 09:48
https://doi.org/10.1007/978-3-322-85564-0 of FLRs, determination of weight for each FLR, and defuzzification of fuzzified time series values. To resolve the problem associated with the determination of length of intervals, this study suggests a new time series data discretization technique. After generating the intervals, the historical ti作者: GRAIN 時(shí)間: 2025-3-23 14:08 作者: diskitis 時(shí)間: 2025-3-23 21:11
Allgemeine Pharmakologie der Muskeln In this chapter, we introduce a model to deal with forecasting problems of two-factors. The proposed model is designed using FTS and ANN. In a FTS, the length of intervals in the universe of discourse always affects the results of forecasting. Therefore, an ANN based technique is employed for deter作者: Fecundity 時(shí)間: 2025-3-24 01:17
https://doi.org/10.1007/978-3-663-07194-5n forecasting models. Therefore, in this chapter, we have intended to introduce a new Type-2 FTS model that can utilize more observations in forecasting. Later, this Type-2 model is enhanced by employing PSO technique. The main motive behind the utilization of the PSO with the Type-2 model is to adj作者: labyrinth 時(shí)間: 2025-3-24 04:01 作者: GRIN 時(shí)間: 2025-3-24 10:19 作者: 制定 時(shí)間: 2025-3-24 11:42
https://doi.org/10.1007/978-3-319-26293-2Fuzzy Time Series Modeling; Type 2 Fuzzy Time Series Model; Hybrid Neuro-fuzzy Models; FTS-PSO Model; M-作者: 死貓他燒焦 時(shí)間: 2025-3-24 16:23 作者: Frenetic 時(shí)間: 2025-3-24 22:11 作者: 牲畜欄 時(shí)間: 2025-3-25 02:13 作者: 公豬 時(shí)間: 2025-3-25 05:26
Introduction,As the application of information technology is growing very rapidly, data in various formats have also proliferated over the time.作者: novelty 時(shí)間: 2025-3-25 11:10 作者: 吝嗇性 時(shí)間: 2025-3-25 12:22 作者: 一回合 時(shí)間: 2025-3-25 16:16 作者: 乳白光 時(shí)間: 2025-3-25 20:04
High-Order Fuzzy-Neuro Time Series Forecasting Model,f forecasting. So, for creating the effective lengths of intervals of the historical time series data set, a new “Re-Partitioning Discretization (RPD)” approach is introduced in the proposed model. Many researchers suggest that high-order fuzzy relationships improve the forecasting accuracy of the m作者: 未開(kāi)化 時(shí)間: 2025-3-26 03:53
Two-Factors High-Order Neuro-Fuzzy Forecasting Model, In this chapter, we introduce a model to deal with forecasting problems of two-factors. The proposed model is designed using FTS and ANN. In a FTS, the length of intervals in the universe of discourse always affects the results of forecasting. Therefore, an ANN based technique is employed for deter作者: 試驗(yàn) 時(shí)間: 2025-3-26 06:01
FTS-PSO Based Model for M-Factors Time Series Forecasting,n forecasting models. Therefore, in this chapter, we have intended to introduce a new Type-2 FTS model that can utilize more observations in forecasting. Later, this Type-2 model is enhanced by employing PSO technique. The main motive behind the utilization of the PSO with the Type-2 model is to adj作者: TOM 時(shí)間: 2025-3-26 11:23 作者: xanthelasma 時(shí)間: 2025-3-26 16:13
https://doi.org/10.1007/978-3-322-85564-0also identified various domains specific problems and research trends, and try to categorize them. The chapter ends with the implication for future works. This review may serve as a stepping stone for the amateurs and advanced researchers in this domain.作者: interference 時(shí)間: 2025-3-26 17:48
https://doi.org/10.1007/978-3-322-85564-0st. Therefore, in this model, it is recommended to consider the repeated FLRs during forecasting. It is also suggested to assign weights on the FLRs based on their severity rather than their patterns of occurrences. For this purpose, a new technique is incorporated in the model. This technique deter作者: inundate 時(shí)間: 2025-3-27 00:56 作者: Ethics 時(shí)間: 2025-3-27 01:18
https://doi.org/10.1007/978-3-663-07194-5sarathy (.) (1871–1994) and IITM (.) (1995–2010) for the period 1871–2010, for the months of June, July, August and September individually, and for the monsoon season (sum of June, July, August and September). The data set is trained and tested separately for each of the neural network architecture,作者: ICLE 時(shí)間: 2025-3-27 05:16
Applications of Soft Computing in Time Series ForecastingSimulation and Model作者: Hypopnea 時(shí)間: 2025-3-27 10:40 作者: Cultivate 時(shí)間: 2025-3-27 14:03 作者: collagenase 時(shí)間: 2025-3-27 21:09 作者: Anonymous 時(shí)間: 2025-3-27 22:02 作者: 嘴唇可修剪 時(shí)間: 2025-3-28 05:01 作者: Engaged 時(shí)間: 2025-3-28 07:46
10樓作者: Permanent 時(shí)間: 2025-3-28 13:32
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