A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on ...

This paper introduces the “Energy-Environmental Efficiency” concept of building a low-carbon dispatch model of wind-incorporated power systems from the perspective of environmental protection and low-carbon dispatch promotion based on the existing economic environmental dispatch. A rolling auto-regressive and moving-average model is adopted to forecast wind speeds for the next 24 h and reduce t...

OBJECTIVE To evaluate the effectiveness of an adherence promotion intervention provided to patients and families referred to a clinical service. METHODS 6 patients and their caregivers representing 5 different chronic conditions were seen for comprehensive psychological intervention that was evaluated based on electronic monitoring of adherence to prescribed oral medication. RESULTS Time se...

Received Jul 22, 2012 Revised Oct 23, 2012 Accepted Nov 14, 2012 Time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. Auto-Regressive Integrated Moving Average (ARIMA) models are one of the most important time series models used in financial market forecasting over the past three decades but not very often used to forec...

In this paper, we present the use of different mathematical models to forecast service requests in support centers (SCs). A successful prediction of service request can help in the efficient management of both human and technological resources that are used to solve these eventualities. A nonlinear analysis of the time series indicates the convenience of nonlinear modeling. Neural models based ...

Security problems with network are significant, such as network failures and malicious attacks. Monitoring network traffic and detect anomalies of network traffic is one of the effective manner to ensure network security. In this paper, we propose a hybrid method for network traffic prediction and anomaly detection. Specifically, the original network traffic data is decomposed into high-frequen...

An approach to handling colored observation noise in large least-squares (LS) problems is presented. The handling of colored noise is reduced to the problem of solving a Toeplitz system of linear equations. The colored noise is represented as an auto regressive moving-average (ARMA) process. Stability and invertability of the ARMA model allows the solution of the Toeplitz system to be reduced t...

To begin a zero accident campaign for industry, the first thing is to estimate the industrial accident rate and the zero accident time systematically. This paper considers the social and technical change of the business environment after beginning the zero accident campaign through quantitative time series analysis methods. These methods include sum of squared errors (SSE), regression analysis ...

The application of multivariate time series is so large,it can be used in many systems, like ecnomic systems,biological systems, and so on.This paper introduced the method’s building and the structure of ARIMAX model (auto-regressive integrated moving average model with explanatory variables) and its SAS realizing. The paper analysed the tertiaryindustry in China with the realty business to be ...

The dynamic response analysis of structures subjected to a stochastic wind field is carried out in the time domain by a step-by-step integration approach. The loading is represented by simulated time histories of the aerodynamic force. The auto-regressive and moving average (ARMA) recursive models are utilized to simulate time series of wind loads. Depending on the system dynamic characteristic...