scholarly journals A Consumer Behavior Prediction Model Based on Multivariate Real-Time Sequence Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Lin Guo ◽  
Ben Zhang ◽  
Xin Zhao
Keyword(s):  
Consumer Behavior ◽  
Time Series Data ◽  
Sequence Data ◽  
Rapid Development ◽  
Series Data ◽  
Survey Method ◽  
Behavior Prediction ◽  
Consumption Behavior ◽  
Personal Consumption ◽  
Sampling Survey

With the rapid development of online finance and social networks, a large amount of behavioral data is stored on the Internet, which can fully reflect the shopping tendencies and habits of real users. Using big data to analyze consumer behavior is more scientific and accurate than the traditional sampling survey method. Internet consumption behavior data are time series data. Therefore, this paper proposes a method of analyzing behavioral sequence data, which learns personal consumption interests and habits, and finally predicts payment behavior. The experiments compare the execution effect of different algorithms on multiple databases and verify the feasibility and effectiveness of the proposed algorithm SeqLearn.

scholarly journals PERILAKU KONSUMSI ISLAM DI INDONESIA

2017 ◽  
Vol 2 (1) ◽  
pp. 91-106
Author(s):  
Novi Indriyani Sitepu
Keyword(s):  
Time Series ◽  
Qualitative Method ◽  
Time Series Data ◽  
Series Data ◽  
Consumption Behavior ◽  
Analysis Techniques ◽  
Library Research ◽  
Public Consumption ◽  
Consumptive Behavior ◽  
Islamic Values

This study aims to analyze the urgency of consumption in the economy and the implementation of Islamic values in public consumption behavior. The data used was time series data to food consumption on Indonesian from year 2011 to 2014. The analysis was conducted with qualitative method using the analysis techniques library research, are deskriptive analysis. The result shows that consumptive behavior becomes a habit Indonesian society, so the community income mostly just for consumption. Islam provides a solution that balanced consumption behavior that is not tabdjir and not ishraf.Artikel ini bertujuan untuk menganalisis tentang urgensi konsumsi dalam perekonomian dan implementasi nilai Islam pada perilaku konsumsi masyarakat. Data yang digunakan adalah data seri waktu (time series) terhadap konsumsi makanan di Indonesia dari tahun 2011 sampai dengan 2014. Analisis dilakukan dengan metode kualitatif dengan menggunakan tekhnik analisis library research yang bersifat deskriptif analisis. Hasil-hasil penelitian menunjukkan bahwa Perilaku konsumtif menjadi kebiasaan masyarakat Indonesia, sehingga penghasilan masyarakat sebagian besar hanya untuk konsumsi. Islam menawarkan pola konsumsi yang seimbang yaitu tidak tabdjir dan tidak ishraf.

EFFECTS OF GOVERNMENT HEALTH EXPENDITURES ON THE PERFORMANCE OF HEALTH SECTOR IN NIGERIA (1979-2017). AN EMPIRICAL ANALYSIS

2020 ◽  
Vol 12 (2) ◽  
pp. 87-102
Author(s):  
Panan Danladi Gwaison ◽  
Livinus Nkuri Maimako
Keyword(s):  
Life Expectancy ◽  
Health Expenditure ◽  
Time Series Data ◽  
Rapid Development ◽  
Health Sector ◽  
Unit Root Test ◽  
Health Expenditures ◽  
Series Data ◽  
Development Indicators ◽  
Government Health

Health is a very important aspect of an individual’s wellbeing, and since individuals make a nation, therefore, healthcare expenditure could be regarded as one of the necessary conditions to achieving a sustainable long-term economic development. This study examined the effects of government health expenditures on the performance of health Sector in Nigeria. The study employed expo facto research design. The annual time series data from 1979 to 2017 was used in this study from Statistical Bulletin of the Central Bank of Nigeria and World Development Indicators, 2018. The pre estimation test like the descriptive statistics, Augmented Dickey-Fuller (ADF) unit root test Johensen cointegration test and Error correction model test. The OLS estimation technique was used to determine the coefficient of the variables and test the four hypothesis. The results indicated that government total health expenditures, capital health expenditure and recurrent health expenditures are positively related to the performance of health sector proxy by life expectancy rate and statistically insignificant. However capital health expenditure was statistically significant to life expectancy. The study recommends that more emphasis should be placed on the capital expenditures on health as this will facilitate rapid development of the sector and adequate Machinery should be put in place by all sectors of government to arrest corruption and penalize those who divert and embezzle public health fund among other recommendations were made.

scholarly journals An Empirical Analysis of Energy Consumption, FDI and High Quality Development Based on Time Series Data of Zhejiang Province

2020 ◽  
Vol 17 (9) ◽  
pp. 3321
Author(s):  
Shaolong Zeng ◽  
Yiqun Liu ◽  
Junjie Ding ◽  
Danlu Xu
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Energy Consumption ◽  
Open Economy ◽  
High Speed ◽  
Time Series Data ◽  
Rapid Development ◽  
Series Data ◽  
High Quality ◽  
The Relationship

This paper aims to identify the relationship among energy consumption, FDI, and economic development in China from 1993 to 2017, taking Zhejiang as an example. FDI is the main factor of the rapid development of Zhejiang’s open economy, which promotes the development of the economy, but also leads to the growth in energy consumption. Based on the time series data of energy consumption, FDI inflow, and GDP in Zhejiang from 1993 to 2017, we choose the vector auto-regression (VAR) model and try to identify the relationship among energy consumption, FDI, and economic development. The results indicate that there is a long-run equilibrium relationship among them. The FDI inflow promotes energy consumption, and the energy consumption promotes FDI inflow in turn. FDI promotes economic growth indirectly through energy consumption. Therefore, improving the quality of FDI and energy efficiency has become an inevitable choice to achieve the transition of Zhejiang’s economy from high speed growth to high quality growth.

scholarly journals Tracking and Classifying Global COVID-19 Cases by using 1D Deep Convolution Neural Networks

2020 ◽  
Author(s):  
Mark Amo-Boateng
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Time Series Data ◽  
Sequence Data ◽  
Series Data ◽  
The Novel ◽  
Response Curves ◽  
Convolution Neural Networks ◽  
Link Type ◽  
Novel Coronavirus

ABSTRACTThe novel coronavirus disease (COVID-19) and pandemic has taken the world by surprise and simultaneously challenged the health infrastructure of every country. Governments have resorted to draconian measures to contain the spread of the disease despite its devastating effect on their economies and education. Tracking the novel coronavirus 2019 disease remains vital as it influences the executive decisions needed to tighten or ease restrictions meant to curb the pandemic. One-Dimensional (1D) Convolution Neural Networks (CNN) have been used classify and predict several time-series and sequence data. Here 1D-CNN is applied to the time-series data of confirmed COVID-19 cases for all reporting countries and territories. The model performance was 90.5% accurate. The model was used to develop an automated AI tracker web app (AI Country Monitor) and is hosted on https://aicountrymonitor.org. This article also presents a novel concept of pandemic response curves based on cumulative confirmed cases that can be use to classify the stage of a country or reporting territory. It is our firm believe that this Artificial Intelligence COVID-19 tracker can be extended to other domains such as the monitoring/tracking of Sustainable Development Goals (SDGs) in addition to monitoring and tracking pandemics.

Data mining model for multimedia financial time series using information entropy

2020 ◽  
Vol 39 (4) ◽  
pp. 5339-5345
Author(s):  
Han He ◽  
Yuanyuan Hong ◽  
Weiwei Liu ◽  
Sung-A Kim
Keyword(s):  
Data Mining ◽  
Time Series ◽  
Time Series Data ◽  
Financial Time Series ◽  
Rapid Development ◽  
Development Trend ◽  
Series Data ◽  
Transaction Data ◽  
Relationship Analysis ◽  
Financial Time

At present, KDD research covers many aspects, and has achieved good results in the discovery of time series rules, association rules, classification rules and clustering rules. KDD has also been widely used in practical work such as OLAP and DW. Also, with the rapid development of network technology, KDD research based on WEB has been paid more and more attention. The main research content of this paper is to analyze and mine the time series data, obtain the inherent regularity, and use it in the application of financial time series transactions. In the financial field, there is a lot of data. Because of the huge amount of data, it is difficult for traditional processing methods to find the knowledge contained in it. New knowledge and new technology are urgently needed to solve this problem. The application of KDD technology in the financial field mainly focuses on customer relationship analysis and management, and the mining of transaction data is rare. The actual work requires a tool to analyze the transaction data and find its inherent regularity, to judge the nature and development trend of the transaction. Therefore, this paper studies the application of KDD in financial time series data mining, explores an appropriate pattern mining method, and designs an experimental system which includes mining trading patterns, analyzing the nature of transactions and predicting the development trend of transactions, to promote the application of KDD in the financial field.

PENGARUH SUBSIDI INPUT TERHADAP NILAI TUKAR PETANI PADI DI INDONESIA

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Redy Prasetyo ◽  
R. N. Afsdy Saksono
Keyword(s):  
Path Analysis ◽  
Time Series Data ◽  
National Level ◽  
Secondary Data ◽  
Terms Of Trade ◽  
Series Data ◽  
Survey Method ◽  
National Data ◽  
Agricultural Input ◽  
Paddy Yield

This study aimed to determine how impact of the agricultural input subsidy on farmer terms of trade in Indonesia. This study used a quantitative approach with survey method on time series data of each variable analyzed. Research variables were seed subsidy, fertilizer subsidy, paddy yield and farmer terms of trade. The data used are secondary data from 2009-2015. The analytical method employed was path analysis was applied to the analysis of the national data. The results of path analysis showed that at the national level, seed subsidies affect NTP negatively. Fertilizer subsidies analysis at the national level, also showed negative affect on NTP.Keywords: seed subsidy, fertilizer subsidy, productivity, farmer terms of trade, path analysis

Analysis of attention on venture capital: A method of complex network on time series

2020 ◽  
Vol 34 (29) ◽  
pp. 2050273
Author(s):  
Yu-Jie Zhang ◽  
Kou Meng ◽  
Ting Gao ◽  
Yan-Qiu Song ◽  
Jun Hu ◽  
...  
Keyword(s):  
Time Series ◽  
Venture Capital ◽  
Time Series Data ◽  
Rapid Development ◽  
Mobile Terminal ◽  
Peak Effect ◽  
Social Progress ◽  
Series Data ◽  
Network Characteristics ◽  
Policy Guidance

Venture capital is an important force in promoting technological innovation and social progress. Research regarding the attention on venture capital can help understand the development and social influence of venture capital, which is conducive to the policy guidance and incentive to the industry. With the rapid development of information technology, the Internet has become the main source and dissemination channel of information, and search engines have become an important interface for information. Through a deep analysis of the search index of venture capital, we can find information that is more important. Based on the principle of time series visualization, we have transformed the time series data of attention on venture capital into complex networks and analyzed its network characteristics. We collected the Baidu index of Chinese venture capital from January 1, 2018 to November 25, 2019 and constructed a time series network based on PC plus mobile search, PC search, and mobile search. The results show that the convenience of the mobile terminal offers makes it the primary mode of tracking the industrial dynamics of venture capital, especially hot news. Relatively, PC terminal search is more stable than mobile search, more focused on industry reports, and refers to long-term followers of venture capital. Both degree distribution and centrality distribution of the three networks show that abnormal peaks and lows are few and the number of key time points in the time series of search on venture capital is insignificant. However, the clustering results show obvious segmentation effect that the peak effect of hot news is evident.

scholarly journals Analysis of The Relationship Between Income Inequality snd Poverty Prevalence in Selected North Central States of Nigeria: 1991 – 2013

2018 ◽  
Vol 5 (3) ◽  
pp. 22
Author(s):  
Ndako Yahaya Shaba ◽  
S. A. J. Obansa ◽  
Sule Magaji ◽  
Mohammed Yelwa
Keyword(s):  
Income Inequality ◽  
Poverty Alleviation ◽  
Time Series Data ◽  
Good Governance ◽  
Empirical Relationship ◽  
Series Data ◽  
Survey Method ◽  
Calorie Intake ◽  
Poverty Level ◽  
North Central

Poverty in Nigeria has been described as pervasive owing to the fact that the nation has witnessed a persistent increase in poverty level over the years despite various poverty alleviation programs. More so, it has been argued that income inequality is a manifestation as well as strong cause of poverty. The study therefore analyses the empirical relationship between income inequality and poverty prevalence among households in selected North Central States in Nigeria. This study employed survey method supported by time series data using regression analysis A representative sample of 600 respondents was planned for the survey in order to have at least 462 households responding. The result shows that dependency ratio, level of calorie intake, poverty per head counts are important factor influencing the level of poverty prevalence. Hence the study observes a substantial correlation between income inequality and poverty prevalence in the studied North Central Nigeria. The study therefore recommends a deliberate policy of reducing income inequality through equitable distribution of income and acceptable revenue sharing formula, need to campaign against large family size, providing subsidy and credit facilities for farmers and artisans true co-operatives, overhauling existing poverty alleviation programme and finally instituting good governance in every sphere of government activity which is a sine-qua-non for poverty reduction.

scholarly journals Microfinance Banks Dynamics Effect on Small-Scale Enterprise Development in Nigeria

2020 ◽  
Vol 6 (2) ◽  
pp. 64
Author(s):  
Adesola, Wasiu Adebisi ◽  
Ewa, Uket Eko ◽  
Arikpo, Oka Felix
Keyword(s):  
Time Series Data ◽  
Series Data ◽  
Survey Method ◽  
Small Scale ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run ◽  
Domestic Savings ◽  
Short Run ◽  
The Government

This study examined the effect of Microfinance Banks on the development of Small and Medium Scale Enterprises in Nigeria. This study was specifically meant to assess the extent to which microfinance banks loans and advances, investments and deposit mobilization affect the productivity of SMEs in Nigeria. The study employed the ex-pose facto research design. Time series data were collected from the CBN statistical Bulletin and SMEDAN annual publications using the desk survey method. The data were analysed using the Vector Error Correction Mechanism. Result from the analyses revealed that Microfinance banks loans and advances and investments do not have any significant effect on SMEs’ productivity in Nigeria both in the long run and short run period. The study further reveals that microfinance banks’ deposit mobilization does not have any significant effect on SMEs’ productivity in Nigeria in the long run, however, within the short run period microfinance banks deposits mobilization has a significant effect on SMEs’ productivity. Based on these findings, it was recommended that MFBs should lighten the condition for lending and increase the duration of lending to their customers, spreading the repayment over a long period of time to assist SMEs meet their funding needs. Also, the Government and its institutions, including the Central Bank, should work in concert to promote the sector, as a means of mobilizing domestic savings, widening the financial system, promoting enterprises, creating employment and income and reducing poverty.

scholarly journals A Time Series Analysis - Based Forecasting Approach for the Indian Realty Sector

2021 ◽  
Author(s):  
Jaydip Sen
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Real Time ◽  
Stock Prices ◽  
Time Series Data ◽  
Rapid Development ◽  
Series Data ◽  
Time Processing ◽  
Forecasting Models ◽  
Series Analysis

<p>Prediction of stock prices using time series analysis is quite a difficult and challenging task since the stock prices usually depict random patterns of movement. However, the last decade has witnessed rapid development and evolution of sophisticated algorithms for complex statistical analysis. These algorithms are capable of processing a large volume of time series data executing on high-performance hardware and parallel computing architecture. Thus computations which were seemingly impossible to perform a few years back are quite amenable to real-time time processing and effective analysis today. Stock market time series data are large in volume, and quite often need real-time processing and analysis. Thus it is quite natural that research community has focused on designing and developing robust predictive models for accurately forecasting stochastic nature of stock price movements. This work presents a time series decomposition-based approach for understanding the past behavior of the realty sector of India, and forecasting its behavior in future. While the forecasting models are built using the time series data of the realty sector for the period January 2010 till December 2015, the prediction is made for the time series index values for the months of the year 2016. A detailed comparative analysis of the methods are presented with respect to their forecasting accuracy and extensive results are provided to demonstrate the effectiveness of the six proposed forecasting models. </p>

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