The Use of Time-Series Designs: Interaction between Skill Level and Application

1981 ◽  
Vol 59 (10) ◽  
pp. 621-627 ◽  
Author(s):  
RORY REMER
Keyword(s):  
Time Series ◽  
Skill Level ◽  
Use Of Time

scholarly journals Monitoring distributed computing beyond the traditional time-series histogram

2020 ◽  
Vol 245 ◽  
pp. 03036
Author(s):  
M S Doidge ◽  
P. A. Love ◽  
J Thornton
Keyword(s):  
Time Series ◽  
Distributed Computing ◽  
Real Time ◽  
A Priori ◽  
Time Data ◽  
Use Of Time ◽  
Computing Services ◽  
Monitoring Tools ◽  
Novel Approach ◽  
Current Monitoring

In this work we describe a novel approach to monitor the operation of distributed computing services. Current monitoring tools are dominated by the use of time-series histograms showing the evolution of various metrics. These can quickly overwhelm or confuse the viewer due to the large number of similar looking graphs. We propose a supplementary approach through the sonification of real-time data streamed directly from a variety of distributed computing services. The real-time nature of this method allows operations staff to quickly detect problems and identify that a problem is still ongoing, avoiding the case of investigating an issue a-priori when it may already have been resolved. In this paper we present details of the system architecture and provide a recipe for deployment suitable for both site and experiment teams.

Load Forecasting using Time Series Techniques

2021 ◽  
pp. 11343-11357
Author(s):  
Shahida Khatoon, Ibraheem, Priti, Mohammad Shahid
Keyword(s):  
Time Series ◽  
Linear Models ◽  
Linear Trend ◽  
Moving Average ◽  
Load Forecasting ◽  
Electric Load ◽  
Time Data ◽  
Efficient Operation ◽  
Use Of Time ◽  
Distribution Company

Load Forecasting is of great significance for effective and efficient operation of power system. Use of time series is of much importance in load forecasting. In this study, effectiveness of different time series techniques is identified to gathered valuable information. The objective is to predict electric load efficiently and effectively. This paper analyses the prediction accuracy of variety of time series method in modeling Electric load forecasts. The study examines the time series forecasting methods applied to estimate future electric load, specifically, Moving Average (MA), Linear Trend, the Exponential and Parabolic Trend. A comparison of different forecasting techniques of Time Series is demonstrated on real time data. The data utilized for forecast is made available through a distribution company of India. The traditional linear models and hybrid models along with ANN are developed. These models are appraised for the forecasting capability.

Time Series Forecasting in Retail Sales Using LSTM and Prophet

2021 ◽  
pp. 241-262
Author(s):  
Clony Junior ◽  
Pedro Gusmão ◽  
José Moreira ◽  
Ana Maria M. Tome
Keyword(s):  
Time Series ◽  
Data Science ◽  
Short Term Memory ◽  
Special Kind ◽  
Time Series Forecasting ◽  
Short Term ◽  
Term Memory ◽  
Use Of Time

Data science highlights fields of study and research such as time series, which, although widely explored in the past, gain new perspectives in the context of this discipline. This chapter presents two approaches to time series forecasting, long short-term memory (LSTM), a special kind of recurrent neural network (RNN), and Prophet, an open-source library developed by Facebook for time series forecasting. With a focus on developing forecasting processes by data mining or machine learning experts, LSTM uses gating mechanisms to deal with long-term dependencies, reducing the short-term memory effect inherent to the traditional RNN. On the other hand, Prophet encapsulates statistical and computational complexity to allow broad use of time series forecasting, prioritizing the expert's business knowledge through exploration and experimentation. Both approaches were applied to a retail time series. This case study comprises daily and half-hourly forecasts, and the performance of both methods was measured using the standard metrics.

scholarly journals Estimating mass-wasting processes in active earth slides – earth flows with time-series of High-Resolution DEMs from photogrammetry and airborne LiDAR

2009 ◽  
Vol 9 (2) ◽  
pp. 433-439 ◽  
Author(s):  
A. Corsini ◽  
L. Borgatti ◽  
F. Cervi ◽  
A. Dahne ◽  
F. Ronchetti ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Large Scale ◽  
Airborne Lidar ◽  
Mitigation Measures ◽  
Mass Wasting ◽  
Aerial Photos ◽  
Use Of Time ◽  
Elevation Changes ◽  
Earth Flows

Abstract. This paper deals with the use of time-series of High-Resolution Digital Elevation Models (HR DEMs) obtained from photogrammetry and airborne LiDAR coupled with aerial photos, to analyse the magnitude of recently reactivated large scale earth slides – earth flows located in the northern Apennines of Italy. The landslides underwent complete reactivation between 2001 and 2006, causing civil protection emergencies. With the final aim to support hazard assessment and the planning of mitigation measures, high-resolution DEMs are used to identify, quantify and visualize depletion and accumulation in the slope resulting from the reactivation of the mass movements. This information allows to quantify mass wasting, i.e. the amount of landslide material that is wasted during reactivation events due to stream erosion along the slope and at its bottom, resulting in sediment discharge into the local fluvial system, and to assess the total volumetric magnitude of the events. By quantifying and visualising elevation changes at the slope scale, results are also a valuable support for the comprehension of geomorphological processes acting behind the evolution of the analysed landslides.

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