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Forecast of China’s Forestation Area Based on arima model

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Chinese Forestry Science and Technology 2010年第2期9卷 50-55页

作者： DUAN Wei CHEN WENHUI LI Qiang College of Economics and Management, Beijing Forestry University, Beijing 100083, P.R.China

Man-made forest, which is the forest ecosystem of rehabilitation and reconstruction, plays a significant role in the provision of forest products and improvement the ecological environment. In this paper, we established the AR (5) model to predict China's forest area from 2009 to 2015. This study shows the slow growth of the national plantation area trend with some fluctuations, but the overall growth rate is not large. We proposed that on one hand China should continue to increase the plantation area, on the other hand the quality of plantation should be ensured.

关键词： man-made forest arima model forecast

Forecast on Price of Agricultural Futures in China Based on arima model

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Asian Agricultural Research 2016年第11期8卷 9-12,16页

作者： Chunyang WANG School of Business Macao University of Science and Technology

The forecast on price of agricultural futures is studied in this paper. We use the arima model to estimate the price trends of agricultural futures,which can help the investors to optimize their investing plans. The soybean future contracts are taken as an example to simulate the forecast based on the auto-regression coefficient(p),differential times(d) and moving average coefficient(q). The results show that arima model is better to simulate and forecast the trend of closing prices of soybean futures contract,and it is applicable to forecasting the price of agricultural futures.

关键词： Price of agricultural futures arima model Short-term forecast of price

Prediction and Analysis of O_3 based on the arima model

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Agricultural Science & Technology 2015年第10期16卷 2146-2148页

作者：李双金杨宁闫奕琪曹旭东冀德刚河北农业大学现代科技学院河北保定071000 河北农业大学理学院数学系河北保定071000

The research conducted prediction on changes of atmosphere pollution during July 9, 2014-July 22, 2014 with SPSS based on monitored data of O3 in 13 successive weeks from 6 sites in Baoding City and demonstrated prediction effect of arima model is good by Ljung-Box Q-test and R2, and the model can be used for prediction on future atmosphere pollutant changes.

关键词： Air quality Analysis of time series SPSS arima model

The Application of arima model in Forecasting of PDSI in Henan Province

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Agricultural Science & Technology 2016年第3期17卷 760-764页

作者：厉玉昇河南省气象科学研究所河南郑州450003

[Objective] The aim was to establish drought forecasting model with high precision. [Method] With an arima regression model, the research performed Palmer Drought mode（PDSI） time series modeling analysis of Henan Province based on PDSI time series and DPS（Data Processing Software） in order to build drought forecasting model. [Result] It is feasible to perform drought forecasting with appropriate parameters. [Conclusion] arima model is practical and more precise in PDSI-based drought analysis and forecasting.

关键词： arima model PDSI Forecasting Application Henan Province

Post Millennium Development Goals Prospect on Child Mortality in India: An Analysis Using Autoregressive Integrated Moving Averages (arima) model

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Health 2016年第15期8卷 1845-1872页

作者： Partha De Damodar Sahu Arvind Pandey B. K. Gulati Nomita Chandhiok Arvind Kumar Shukla Pavitra Mohan Raj Gautam Mitra Indian Statistical Institute Kolkata India National Institute of Medical Statistics ICMR Ansari Nagar New Delhi India Indian Council of Medical Research New Delhi India Subharti Medical College Meerut India UNICEF New Delhi India

Background & Objectives: Sustainable Development Goals (SDGs) are set up as a part of the Post Millennium Development Goals (MDGs). Then it becomes essential to review the achievement of the MDGs in India and lessons learned to incorporate into the SDGs. The present study reviews and predicts different components of under-five mortality rate beyond 2015 to assess the present situation and to determine the future possibilities of achieving the new targets for SDGs in India. Data and Methods: It uses available time series data on different components of U5MR from the India’s Sample Registration System (SRS). Autoregressive Integrated Moving Averages (arima) model has been taken as the method of time series analysis to forecast the mortality rates beyond 2015. Results: There is a consistent pattern of faster decline in the under-five mortality compared with the neonatal mortality rate across all major states in India although neonatal mortality contributes largest share in under-five mortality. Again, share of neonatal death among under-five death is increasing steadily over the future projected years. This indicates very slow progress of reduction in neonatal mortality. Stimulating efforts with new intervention programmes will be needed to focus more on lowering neonatal mortality particularly in rural India.

关键词： Under-Five Mortality Infant Mortality Neonatal Mortality Sustainable Development Goals Post-2015 Development Agenda arima model Mortality Projection

Forecasting Tesla’s Stock Price Using the arima model

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Proceedings of Business and Economic Studies 2022年第5期5卷 38-45页

作者： Qiangwei Weng Ruohan Liu Zheng Tao College of Science and Technology Wenzhou-Kean UniversityWenzhou325000Zhejiang ProvinceChina Department of Statistics and Data Science National University of Singapore10 Kent Ridge Crescent 119077Singapore

The stock market is an important economic information *** economic benefits generated by stock price prediction have attracted much *** the stock market cannot be predicted accurately,the stock market’s prediction of the trend of stock prices helps in grasping the operation law of the stock market and the influence mechanism on the *** autoregressive integrated moving average(arima)model is one of the most widely accepted and used time series forecasting ***,this paper first compares the return on investment(ROI)of Apple and Tesla,revealing that the ROI of Tesla is much greater than that of Apple,and subsequently focuses on arima model’s prediction on the available time series data,thus concluding that the arima model is better than the Naïve method in predicting the change in Tesla’s stock price trend.

关键词： Stock price forecast arima model Naïve method Tesla

A hybrid arima-ANN model and its Learning Algorithm on Short-term Load Forecasting

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A hybrid ARIMA-ANN model and its Learning Algorithm on Short...

Forecasting model Based on Information-Granulated GA-SVR and arima for Producer Price Index

第二十三届中国控制会议

作者： Lu Jianchang Niu Dongxiao (Department of Economics and Management, North China Electric Power University, Baoding, 071003)

＜正＞ Because of the complexity of the historical load data and the randomness of a lot of uncertain factors influence, the observed data include the linear and nonlinear parts. The choice of the forecasting model becomes the important influence factor how to improve load forecasting accuracy. arima and ANN are very practical forecasting technology in the short-term electric load forecasting fields. ANN is extensively applied in electric load forecasting especially in recent years. Both arima and ANN have different characteristics. arima is suitable for linear prediction and ANN is suitable for nonlinear prediction. A combined model of arima-ANN is proposed in the text. The linear part of the historical load data can be dealt with arima, and ANN model can deal with the nonlinear part of historical load data. Experimental results indicate that a hybrid arima-ANN model can improve the load forecasting accuracy.

关键词： arima model ANN model Short-term load forecasting hybrid arima-ANN model

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Computers, Materials & Continua 2019年第2期58卷 463-491页

作者： Xiangyan Tang Liang Wang Jieren Cheng Jing Chen Victor S.Sheng Key Laboratory of Internet Information Retrieval of Hainan Province Hainan UniversityHaikou570228China College of Information Science&Technology Hainan UniversityHaikou570228China School of Economic and Management Hainan UniversityHaikou570228China State key laboratory of Marine Resource Utilization in South China Sea Haikou570228China Department of Computer Science University of Central ArkansasConwayAR 72035USA

The accuracy of predicting the Producer Price Index(PPI)plays an indispensable role in government economic ***,it is difficult to forecast the *** our research,we first propose an unprecedented hybrid model based on fuzzy information granulation that integrates the GA-SVR and arima(Autoregressive Integrated Moving Average model)*** fuzzy-information-granulation-based GA-SVR-arima hybrid model is intended to deal with the problem of imprecision in PPI *** proposed model adopts the fuzzy information-granulation algorithm to pre-classification-process monthly training samples of the PPI,and produced three different sequences of fuzzy information granules,whose Support Vector Regression(SVR)machine forecast models were separately established for their Genetic Algorithm(GA)optimization ***,the residual errors of the GA-SVR model were rectified through arima modeling,and the PPI estimate was *** shows that the PPI value predicted by this hybrid model is more accurate than that predicted by other models,including arima,GRNN,and GA-SVR,following several comparative *** also indicates the precision and validation of the PPI prediction of the hybrid model and demonstrates that the model has consistent ability to leverage the forecasting advantage of GA-SVR in non-linear space and of arima in linear space.

关键词： Data analysis producer price index fuzzy information granulation arima model support vector model.

Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

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Computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa Sami Khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim S.K.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVirginia24060USA Delta Higher Institute for Engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research Center MeridenConnecticut06450USA School of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the arima model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization arima model BER algorithm metaheuristic algorithms