Neural network ensemble operators for time series forecasting

Electricity price time series forecasting in deregulated markets using recurrent neural network based approaches

Electricity price time series forecasting in deregulated markets using recurrent neural network based approaches
... Summary Electricity Price Time Series Forecasting in Deregulated Markets Using Recurrent Neural Network Based Approaches In the past decade, electricity price time series system originating from ... electricity price time series and incorporates them for developing RNN based pure as well as hybrid models for modeling electricity price time series and accurate prediction of price in spiking ... Srinivasan, “Novel method of recurrent neural networks learning using invariant features of time series, in IEEE Transactions on Neural Network, accepted • Vishal Sharma and D Srinivasan, “Price...
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Báo cáo hóa học: "Research Article Neural Network Adaptive Control for Discrete-Time Nonlinear Nonnegative Dynamical Systems" ppt

Báo cáo hóa học:
... Neuroadaptive control for discrete-time nonlinear nonnegative uncertain systems In this section, we consider the problem of characterizing neuroadaptive feedback control laws for discrete-time nonlinear ... Chellaboina, Neural network adaptive control for nonlinear nonnegative dynamical systems,” IEEE Transactions on Neural Networks, vol 16, no 2, pp 399–413, 2005 A Berman and R J Plemmons, Nonnegative ... and N Hovakimyan, “Passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems,” IEEE Transactions on Neural Networks, vol 16, no 2, pp 387–398,...
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Tài liệu Fuzzy Neural Network and Wavelet for Tool Condition Monitoring ppt

Tài liệu Fuzzy Neural Network and Wavelet for Tool Condition Monitoring ppt
... 15 Fuzzy Neural Network and Wavelet for Tool Condition Monitoring 15.1 15.2 15.3 15.4 15.5 Xiaoli Li Harbin Institute of Technology Introduction Fuzzy Neural Network Wavelet Transforms Tool ... Transforms Tool Breakage Monitoring with Wavelet Transforms Identification of Tool Wear States Using Fuzzy Methods 15.6 Tool Wear Monitoring with Wavelet Transforms and Fuzzy Neural Network 15.1 Introduction ... as wavelet transforms [2], fuzzy inference [3–5], fuzzy neural networks [6–9], etc., have been established, in which all forms of tool condition can be monitored Fuzzy systems and neural networks...
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Báo cáo khoa học: "Neural Network Probability Estimation for Broad Coverage Parsing" doc

Báo cáo khoa học:
... history-based probability model is choosing a method for estimating the parameters d,_1) The main difficulty with this estimation is that the history d , , di _ is of unbounded length Most probability estimation ... (becoming [S-VP ]) These transforms are undone before any evaluation is performed on the output trees We not believe these transforms have a major impact on performance, but we have not currently ... method for automatically inducing a finite set of features for representing the derivation history The method is a form of multi-layered artificial neural network called Simple Synchrony Networks...
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neural network retinal model real time implementation

neural network retinal model real time implementation
... I I Neural Network Retinal Model Real Time Implementation Acvuqaion For -I , : : Final Report September 1992 I_,_-Di tr! ... project has been to take a significant neural network vision application and to map it onto dedicated hardware for real time implementation The neural network was already demonstrated using software ... specific military tracking application using the neural network retinal modeL 2.0 Neural Network Retinal Model _I I The retina model consists of a number of layers of processing elements, or...
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Báo cáo hóa học: " Research Article An Energy-Based Similarity Measure for Time Series" ppt

Báo cáo hóa học:
... similarity measure would show, for example, that the similarity values between f1 and f2 and that between f3 and f2 are different Results of the SimilB, the ED, and the CC between f2 and f1 and that ... (18) where η and (t) are drawn from a standard normal distribution N (0, 1), a is an integer drawn uniformly from the range [16, 32], and (b − a) is an integer drawn uniformly from the range [32, ... Relative change of amplitude and the corresponding temporal information are well suited to measure similarity between TSs In this paper, a new nonlinear similarity measure for TS analysis, SimilB,...
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ARTIFICIAL NEURAL NETWORK BASED DSS FOR GAME ONLINE PUBLISHING IN VIETNAM

ARTIFICIAL NEURAL NETWORK BASED DSS FOR GAME ONLINE PUBLISHING IN VIETNAM
... offline… Nhà phát hành Thu thập liệu Từ trang tin game tiếng : playpark.vn, gamek.vn, gamethu.vnexpress.net… Từ diễn đàn game: http://forum.gamevn.com/; http://www.gameviet24h.net/ ; Neural networks ... công nghiệp game online VN Sự bão hòa tựa game lựa chọn ngày khắc khe game thủ Nhu cầu khảo sát doanh nghiệp trước phát hành tựa game • Phạm vi tìm hiểu: Artificial Neural Network- based Decision ... trường game online VN • Ý nghĩa thực tiễn • • • Hỗ trợ doanh nghiệp game có nhu cầu định phát hành tựa game Nâng cao chất lượng game, thỏa mãn nhu cầu game thủ Thúc đẩy phát triển thị trường game online...
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Adaptive neural network control of discrete time nonlinear systems

Adaptive neural network control of discrete time nonlinear systems
... organization of this thesis are presented in Sections 1.2, 1.3 and 1.4 respectively 1.1 Adaptive Neural Network Control of Nonlinear Systems 1.1 1.1.1 Adaptive Neural Network Control of Nonlinear Systems ... List of Figures ix List of Tables xii Introduction 1.1 Adaptive Neural Network Control of Nonlinear Systems 1.1.1 Neural Networks 1.1.2 Adaptive NN Control of Continuous -time ... modelling and control of nonlinear systems For neural network controller design of general nonlinear systems, several researchers have suggested to use neural networks as emulators of inverse systems...
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Support vector machine in chaotic hydrological time series forecasting

Support vector machine in chaotic hydrological time series forecasting
... chaos and chaotic techniques In addition, more recent approaches in forecasting chaotic time series are reviewed Review of Support Vector Machine (SVM), a relatively new machine learning tool ... attempts to demonstrate the promising applications of a relatively new machine learning tool, support vector machine, on chaotic hydrological time series forecasting The ability to achieve high ... SUPPORT VECTOR MACHINE IN CHAOTIC HYDROLOGICAL TIME SERIES FORECASTING YU XINYING (M SC., UNESCO-IHE, DISTINCTION) A THESIS SUBMITTED FOR THE DEGREE...
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Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers

Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers
... of processes inside the gasifier In some cases Please cite this article in press as: Mikulandric´ R et al Artificial neural network modelling approach for a biomass gasification process in fixed bed ... different modelling approaches Process modelling approach Advantages Disadvantages Kinetic models More realistic process description Extensive information regarding process operation All possible process ... measurements Please cite this article in press as: Mikulandric´ R et al Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers Energy Convers Manage...
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Tài liệu Evolving the neural network model for forecasting air pollution time series pdf

Tài liệu Evolving the neural network model for forecasting air pollution time series pdf
... (Section 2.5) was used for evolving the MLP for the forecasting problem (Fig 3) The starting populations were initialised with the random set of MLP models (see the encoding in the Section 2.4) and ... adequate information for achieving the performance described in the results Results 3.2 Validation statistics 3.1 Evolved MLP models The validation statistics is presented for each model and the reference ... Therefore, it can be stated the evolving of model inputs and high-level architecture itself could not improve the performances of the models significantly However, more robust and reasonable models...
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Báo cáo hóa học: " Research Article Validity-Guided Fuzzy Clustering Evaluation for Neural Network-Based Time-Frequency Reassignment" potx

Báo cáo hóa học:
... values of these validity measures for fuzzy clustering the GustafsonKessel clustering has the very best results The GustafsonKessel fuzzy clustering algorithm forces each cluster to adapt the ... clusters, and fuzzy clustering is often better suited for the data In this way, data on the boundaries between several clusters are not forced to belong to one of the clusters 2.1 Fuzzy Clustering ... computations for each adjacent pair of components present in the signal indicated by subscript n The value of the measure Ri will be close to one for good performing TFDs and zero for poor performing...
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Adaptive modeling and forecasting for high dimensional time series

Adaptive modeling and forecasting for high dimensional time series
... data series and expand the parameter space to a very high dimension For such high- dimensional time series modeling, the challenges of high dimensionality in space and non-stationary dynamics in time ... even high- dimensional scenarios In this thesis, we are motivated to study adaptive modeling for multivariate and high- dimensional time series under the existence of non-stationarity Three adaptive ... high- dimensional data sets are observed with the evolution of time, multivariate and high- dimensional time series modeling naturally attract massive research and empirical interest However, high...
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Tài liệu A neural-network-based space-vector PWM controller for a three-level voltage-fed inverter induction motor drive doc

Tài liệu A neural-network-based space-vector PWM controller for a three-level voltage-fed inverter induction motor drive doc
... signals are compared with the output of a single UP/DOWN counter and processed through a logic block to generate the PWM outputs for for for for for (5) for for for for for for for for for for ... -phase P states and performed with the and signals only Similar operations are signals of all the phases and all the The drive performance was evaluated in detail by simulation with the neural ... drive and evaluated thoroughly for steady-state and dynamic performance with a conventional DSP-based SVM The performance of the ANN-based modulator was found to be excellent The modulator can...
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