Investigating Water Quality Data Using Principal Component Analysis and Granger Causality

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multivariate Granger causality analysis of fMRI data.

This article describes the combination of multivariate Granger causality analysis, temporal down-sampling of fMRI time series, and graph theoretic concepts for investigating causal brain networks and their dynamics. As a demonstration, this approach was applied to analyze epoch-to-epoch changes in a hand-gripping, muscle fatigue experiment. Causal influences between the activated regions were a...

متن کامل

Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

Driving fatigue has been identified as one of the main factors affecting drivers' safety. The aim of this study was to analyze drivers' different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers' fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under dif...

متن کامل

Power Quality Data Compression Using Principal Component Analysis

With the increasing of non-linear, burst or un-balanced load, power quality issues in the grid is becoming important. With more power quality monitors installed with higher sampling rates, an expanded size of power quality data brings difficulty to storage, transmission and analysis. In this paper, principal component analysis (PCA), which is a popular feature extraction algorithm in pattern re...

متن کامل

Water quality assessment using SVD-based principal component analysis of hydrological data

Principal component analysis (PCA) based on singular value decomposition (SVD) of hydrological data was tested for water quality assessment. Using two case studies of wasteand drinking water, PCA via SVD was able to find latent variables which explain 80.8% and 83.7% of the variance, respectively. By means of scatter and loading plots, PCA revealed the relationships among samples and hydrochemi...

متن کامل

Feature Dimension Reduction of Multisensor Data Fusion using Principal Component Fuzzy Analysis

These days, the most important areas of research in many different applications, with different tools, are focused on how to get awareness. One of the serious applications is the awareness of the behavior and activities of patients. The importance is due to the need of ubiquitous medical care for individuals. That the doctor knows the patient's physical condition, sometimes is very important. O...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Water

سال: 2021

ISSN: 2073-4441

DOI: 10.3390/w13030343