Analytics over Multi-sensor Time Series Data – A Case-Study on Prediction of Mining Hazards

Producers' Response to Changes in Prices and Marketing Policies: A Case Study of Sugarcane and Paddy in Eastern U.P. by S. C. Gupta and A. Majid. New York: Asia Publishing House, 1965.

The Pakistan Development Review ◽

10.30541/v8i2pp.308-309 ◽

1968 ◽

Vol 8 (2) ◽

pp. 308-309

Author(s):

Mohammad Irshad Khan

Keyword(s):

New York ◽

Time Series ◽

Time Series Data ◽

Publishing House ◽

Economic Incentives ◽

The Other ◽

Series Data ◽

Poor Countries ◽

Northern India

It is alleged that the agricultural output in poor countries responds very little to movements in prices and costs because of subsistence-oriented produc¬tion and self-produced inputs. The work of Gupta and Majid is concerned with the empirical verification of the responsiveness of farmers to prices and marketing policies in a backward region. The authors' analysis of the respon¬siveness of farmers to economic incentives is based on two sets of data (concern¬ing sugarcane, cash crop, and paddy, subsistence crop) collected from the district of Deoria in Eastern U.P. (Utter Pradesh) a chronically foodgrain deficit region in northern India. In one set, they have aggregate time-series data at district level and, in the other, they have obtained data from a survey of five villages selected from 170 villages around Padrauna town in Deoria.

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A new approach to detect extreme events: a case study using remotely-sensed precipitation time-series data

Remote Sensing Applications Society and Environment ◽

10.1016/j.rsase.2021.100618 ◽

2021 ◽

Vol 24 ◽

pp. 100618

Author(s):

Philipe Riskalla Leal ◽

Ricardo José de Paula Souza e Guimarães ◽

Fábio Dall Cortivo ◽

Rayana Santos Araújo Palharini ◽

Milton Kampel

Keyword(s):

Time Series ◽

Extreme Events ◽

Time Series Data ◽

Remotely Sensed ◽

Series Data ◽

Precipitation Time Series ◽

New Approach

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CAUSAL RELATIONSHIP OF ENERGY CONSUMPTION AND ECONOMIC GROWTH – A CASE STUDY OF PAKISTAN

International Journal of Legal Studies ( IJOLS ) ◽

10.5604/01.3001.0015.2290 ◽

2021 ◽

Vol 9 (1) ◽

pp. 139-164

Author(s):

Saddam Hussain ◽

Chunjiao Yu

Keyword(s):

Economic Growth ◽

Time Series ◽

Energy Consumption ◽

Causal Relationship ◽

Inflation Rate ◽

Time Series Data ◽

Consumer Price Index ◽

Series Data ◽

Relationship Of

This paper explores the causal relationship between energy consumption and economic growth in Pakistan, applying techniques of co-integration and Hsiao’s version of Granger causality, using time series data over the period 1965-2019. Time series data of macroeconomic determi-nants – i.e. energy growth, Foreign Direct Investment (FDI) growth and population growth shows a positive correlation with economic growth while there is no correlation founded be-tween economic growth and inflation rate or Consumer Price Index (CPI). The general conclu-sion of empirical results is that economic growth causes energy consumption.

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An Efficient Anomaly Detection in Quasi-Periodic Time Series Data—A Case Study with ECG

Time Series Analysis and Forecasting - Contributions to Statistics ◽

10.1007/978-3-319-96944-2_10 ◽

2018 ◽

pp. 147-157 ◽

Cited By ~ 1

Author(s):

Goutam Chakraborty ◽

Takuya Kamiyama ◽

Hideyuki Takahashi ◽

Tetsuo Kinoshita

Keyword(s):

Time Series ◽

Anomaly Detection ◽

Time Series Data ◽

Series Data ◽

Periodic Time Series

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Visibility Graph Power Geometric Aggregation Operator and Its Application in Water, Energy and Food Efficiency Evaluation

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17113891 ◽

2020 ◽

Vol 17 (11) ◽

pp. 3891

Author(s):

Lihua Liu ◽

Jing Huang ◽

Huimin Wang

Keyword(s):

Time Series ◽

Time Series Data ◽

Coupling Efficiency ◽

Aggregation Operator ◽

Visibility Graph ◽

Series Data ◽

Efficiency Evaluation ◽

Geometric Operator ◽

The Relationship

In the real decision-making process, there are so many time series values that need to be aggregated. In this paper, a visibility graph power geometric (VGPG) aggregation operator is developed, which is based on the complex network and power geometric operator. Time series data are converted into a visibility graph. A visibility matrix is developed to denote the links among different time series values. A new support function based on the distance of two values are proposed to measure the support degree of each other when the two time series values have visibility. The VGPG operator considers not only the relationship but also the similarity degree between two values. Meanwhile, some properties of the VGPG operator are also investigated. Finally, a case study for water, energy, and food coupling efficiency evaluation in China is illustrated to show the effectiveness of the proposed operator. Comparative analysis with the existing research is also offered to show the advantages of the proposed method.

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