The northern Gulf of Mexico coast is affected by the North Atlantic hurricane season, which causes storm surge disasters every year and brings serious economic losses to southern USA; therefore, it necessary make an accurate advance prediction level. In this paper, a model with simple structure, fast computation speed, results has been constructed based on nonlinear auto-regressive exogenous (N...

This paper compares the performance of Nonlinear Autoregressive Exogenous (NARX) Neural Network and Support Vector Machine (SVM) regression model to predict Air Pollutant Index (API) in Malaysia. Two models namely NARX SVM were developed using API air quality time series data from three monitoring stations: Pasir Gudang, TTDI Jaya Larkin. Hourly parameters collected year 2016 2018 utilized prod...

This paper presents the degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) operated under several conditions based on combination two types data: data from postal fuel cell hybrid electric vehicles equipped with PEMFC and carrying out their delivery missions laboratory. The is wavelet analysis Nonlinear Autoregressive Exogenous Neural Network (NARX). influences historical state...

Bacterial denitrification is expressed in response to the concurrent exogenous signals of low-oxygen tension and nitrate or one of its reduction products. The mechanism by which nitrate-dependent gene activation is effected was investigated in the denitrifying bacterium Pseudomonas stutzeri ATCC 14405. We have identified and isolated from this organism the chromosomal region encoding the two-co...

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measure...

The Nonlinear autoregressive exogenous (NARX) model, which predicts the current value of a time series based upon its previous values as well as the current and past values of multiple driving (exogenous) series, has been studied for decades. Despite the fact that various NARX models have been developed, few of them can capture the long-term temporal dependencies appropriately and select the re...

Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA). This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX). This uses the variables: barom...

This paper investigates the use of non-linear autoregressive exogenous (NARX) artificial neural networks (ANNs) to achieve black-box average dynamic models dc-dc converters capable capturing main converter non-linearities. Non-linearities may include, for example, behavior variations due changes operating point or mode (e.g., discontinuous conduction mode, continuous mode). presents design guid...

Dự báo ngắn hạn sản lượng điện năng mặt trời mái nhà là công cụ thiết yếu trong quá trình vận hành hệ thống một cách hiệu quả. Bài này bày khảo sát về dự của sử dụng các mạng neuron nhân tạo. Dữ liệu được thu thập từ giám với suất và bức xạ ngày 21/04/2022 đến 01/6/2022. Bốn mô hình để gồm: lan truyền thẳng nhiều lớp (MLFF), tự hồi quy phi tuyến tính đa biến ngoại sinh (NARX), bộ nhớ dài-ngắn (...