Journal articles: 'ARLD model'

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Yadav, Dipesh Kumar, Qi Zhang, Xueli Bai, Enliang Li, and Tingbo Liang. "Liver Transplantation for Alcohol-Related Liver Disease (ARLD): An Update on Controversies and Considerations." Canadian Journal of Gastroenterology and Hepatology 2020 (September 17, 2020): 1–6. http://dx.doi.org/10.1155/2020/8862152.

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According to the recent data from the United Network for Organ Sharing database, alcohol-related liver disease (ARLD) accounts to be the most common indication of liver transplantation (LT) waiting lists in the United States among men without hepatocellular carcinoma (HCC). Severe alcoholic hepatitis (AH) is serious and the life-threatening form of ARLD and should be treated timely. However, the LT for severe AH remained to be controversial among the transplant community because of marked interests about the constrained organ supply and the hazard that the AH liver recipient will return to risky drinking. Early LT for ARLD refers for a patient with severe AH undergoing LT who are non-responder to medical treatments. These patients are generally on the existing waiting list but usually followed by 6-month duration of alcohol abstinence. However, the rule of 6-month alcohol abstinence need before the LT is ambiguous. The 6-month alcohol abstinence was consistently defended in light of the compelling fact that it would enable patients to recoup from the intense impacts of alcohol to the liver. In routine, however, the purported “6-month abstinence rule” turned into a surrogate for the forecast of future drinking by ARLD patients for the LT. Careful consideration should be given to the alcohol use disorder of craving and the hazard for recidivism after the LT. As for the current situation, there, urgently, is a specific need of standardized criteria for the evaluation of patients with severe AH for earlier LT. Moreover, further studies are required precisely to develop an accurate prediction model for posttransplant alcohol recidivism. Additionally, development of a standardized protocol for post-LT follow-up and management is further needed. We carefully outlined the published experience with the LT for ARLD in this review.

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Chou, Chun-Mei, Tsu-Chi Shen, Tsu-Chuan Shen, Chien-Hua Shen, and Tzu-Ling Liu. "LEARNING EFFECTIVENESS AMONG TERTIARY STUDENTS USING AUGMENTED REALITY (AR)-BASED FOR ADAPTING TO INDUSTRY 4.0." MATTER: International Journal of Science and Technology 9 (December 30, 2023): 127–41. http://dx.doi.org/10.20319/mijst.2023.9.127141.

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This study aimed to explore the correlation among AR-based learning effectiveness (ARLE), AR learning beliefs (ARLB), creative learning self-efficacy (CLS), and AR learning motivation (ARLM) of tertiary students in Taiwan. Participants had 378 tertiary students who from 15 school, and used path analysis model of the structural equation model (SEM) based on the questionnaire survey. The results show that there is a significant positive correlation between the AR Learning Beliefs (ARLB) and AR Learning Motivation (ARLM) of tertiary student. It is found that higher correlation between ARLB, ARLM and Creative Learning Self-Efficacy (CLS). There was a significant positive correlation between ARLE and ARLB, and can effectively explain ARLE. This study confirms that CLS is an important factor and an impact mediating factor between ARLB and ARLM. In addition, CLS can also influence ARLE through ARLM.

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Mutmainah, Isbandriyati. "The Impact of Final Demand arld Prices on Indonesia's Total - Import: Cointegration and Error Correction Model Analysis." Jurnal Ekonomi dan Pembangunan Indonesia 9, no. 2 (January 1, 2009): 109–25. http://dx.doi.org/10.21002/jepi.v9i2.161.

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This research is aimed to investigate the influence of final demand and price to Indonesian agregate imports in the long-run and short-run. We use analytical technique cointegration test Iohansen procedures for the long-term influence, and Error Correction Model to estimate the short-term influence, by using quarterly time series data period from_1980 to 2004. From the result of cointegration test and Error Correction Model we found that in the long-term, all of final demand components and price except private investment are important I in determining Indonesian agregate imports. The government expenditure variable has the highest influence, while in the short-term all of independent variables except private consumption are important in determining Indonesian agregate imports and foreign price variable has the highest influence.

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Asante Antwi, Henry, Lulin Zhou, Xinglong Xu, and Tehzeeb Mustafa. "A Comparative Analysis of Impact of Universal Two-Child Policy on Maternity Insurance Fund in Jiangsu Province and Guangxi Zhuang AR." Healthcare 9, no. 4 (April 15, 2021): 468. http://dx.doi.org/10.3390/healthcare9040468.

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The maternity insurance fund in some provinces in China has accumulated unprecedented deficit levels. This imminent depletion can cause a catastrophic health crisis for maternal health. This study analyzed the post-policy impact of key factors on maternity insurance income inflow and outflow in Jiangsu Province and Guangxi Zhuang Autonomous Region (AR). We applied Pasera’s ARLD model and VECM Granger Causality Test to establish long- and short-term impact of selected factors that determines the income and expenditure of the maternity insurance fund in the two regions based on data from 2011 to 2019. Our results show that the addition of new births due to the universal two-child policy has increased the per capita utilization of the maternity insurance fund in both areas. We further observed that the impact of the maternity insurance contribution rate to the maternity insurance fund decays with time giving a long-run limited impact in both provinces. Thus the positive impact is stronger in the short term, but in the long term, its influence or contribution to stability of the funds reduces. The positive impact of interest from investment in the maternity insurance fund is however insignificant in both provinces, giving a major cause for concern on its role in maternity insurance fund income generation. In the short term, the contribution rate of the maternity insurance fund must be adjusted upward or the payment base expanded to receive additional contribution from all employees to avoid complete depletion of the fund. In the long term, we recommend the need to replenish the maternity insurance funds through proper investment options for the funds. We further recommend the need to look for other sources of funding social interventions based on existing practices in other countries.

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Mirović, Vera, Branimir Kalaš, and Milica Inđić. "The determinants of government expenditures in Serbia: The application of ARDL model." Anali Ekonomskog fakulteta u Subotici, no. 00 (2023): 20. http://dx.doi.org/10.5937/aneksub2300020m.

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Government expenditures represent one of the most important issues for policymakers both in ordinary and extraordinary conditions. The aim of this paper is to estimate and identify the effects of selected macroeconomic determinants on government expenditures in Serbia from 2002 to 2020. Using the ARDL technique, the empirical findings confirmed that there is a long-run relationship between gross domestic product, government revenues, inflation, and population size and government expenditures for the observed period. The significant and positive effects of explanatory variables are confirmed in the long run, except for inflation, whose impact is not significant in the short run. Specifically, GDP growth, higher inflation rate, greater government revenues and population contribute to the higher government expenditures level. The obtained findings give certain directions to fiscal authorities in creating and defining optimal government expenditures level in the context of influences of chosen macroeconomic variables.

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Lee, Kyung Hee, and Kyung Soo Kim. "Estimation of Tourism Demand using ARDL model." Korean Corporation Management Review 24, no. 4 (August 31, 2017): 59–74. http://dx.doi.org/10.21052/kcmr.2017.24.4.03.

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Mas, André, and Besnik Pumo. "The ARHD model." Journal of Statistical Planning and Inference 137, no. 2 (February 2007): 538–53. http://dx.doi.org/10.1016/j.jspi.2005.12.006.

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Fazli, S., and H. Noor. "Storm-wise sediment yield prediction using hillslope erosion model in semi-arid abundant lands." Soil and Water Research 8, No. 1 (February 6, 2013): 42–48. http://dx.doi.org/10.17221/27/2012-swr.

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Evaluation of soil erosion by existing models is needed as an important tool for managerial purposes in designation of proper water and soil conservation techniques. The present study aimed to assess the applicability of hillslope erosion model (HEM) as one of the newest erosion models for prediction of storm-wise sediment yield in Khosbijan rangeland with 20% slope steepness by using soil erosion standard plots. In order to run the model, runoff depth, land surface cover, soil texture, slope steepness and length were determined for 16 storm events. The results showed that the uncalibrated HEM did not simulate the observed sediment yields properly. Calibration of soil erodibility parameter and developing regression between observed and estimated data indicated that the model was capable of predicting sediment yield in plots by applying soil erodibility parameter of 0.15 with determination coefficient of 0.64 and estimate error of 40%. 

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Rodrigues, Regiane Lopes, and Michele Veríssimo. "Evidências de desindustrialização setorial no Brasil: uma análise por modelos ARDL." Economia e Sociedade 32, no. 2 (May 2023): 355–81. http://dx.doi.org/10.1590/1982-3533.2023v32n2art05.

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Resumo A literatura kaldoriana argumenta que o processo de desindustrialização reduz o potencial de crescimento econômico no longo prazo. Assim, identificar suas causas é de suma importância para a formulação de políticas eficazes. Este artigo investiga as causas de desindustrialização no Brasil em uma perspectiva setorial, com base no conceito de desindustrialização pela reprimarização da economia, cuja perda de participação dos setores industriais nas exportações é justificada, sobretudo, pelos preços das commodities e pela apreciação cambial. Para tanto, são estimados modelos Autorregressivos de Defasagens Distribuídas (ARDL), com dados de 2002 a 2021. Visto que os efeitos das variáveis analisadas são discrepantes entre os setores, os resultados sinalizam que a desindustrialização no Brasil é heterogênea, tanto entre as categorias por intensidade tecnológica quanto entre os setores individuais. Todavia, os efeitos negativos de curto e longo prazos da valorização dos preços das commodities observado em diversos setores corroboram a hipótese de reprimarização da economia.

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Chananet, C., S. Sukparungsee, and Y. Areepong. "The ARL of EWMA Chart for Monitoring ZINB Model Using Markov Chain Approach." International Journal of Applied Physics and Mathematics 4, no. 4 (2014): 236–39. http://dx.doi.org/10.7763/ijapm.2014.v4.290.

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Jang, Ji-Young. "A Study on How an Aging Population Affects the Effectiveness of Fiscal Policy Using an ARDL Model." Korea International Trade Research Institute 19, no. 4 (August 31, 2023): 1–12. http://dx.doi.org/10.16980/jitc.19.4.202308.1.

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Purpose - This paper examines the impact of an aging population on fiscal policy efficiency. Two significant issues arise from Korea’s aging population: old age poverty and the sustainability of government debts. As Korea’s demographic trajectory is similar to that of Japan, it is vital to study fiscal soundness and efficiency from various points of view. Design/Methodology/Approach - The Autoregressive Distributed Lags (ARDL) - EC model was adopted. ARDL shows statistically robust results when the data are a mixture of stationary at the level or the first difference. The data was downloaded from 1994 to 2019 of five OECD countries; Canada, Japan, Spain, Sweden, and Korea. The country selection followed the regime classification of OECD (2012) based on the labor market structure and redistribution effect after tax. Findings - First, the dependency ratio negatively affects the efficiency of fiscal policy. The marginal propensity was suppressed due to the consumption variance in old age cohorts as the dependency ratio increases. Economic agents react to save for future uncertainty when government spending is funded by issuing debt. Second, the long-term elasticities differed among countries, with Korea having the highest at 0.56, followed by Canada at 0.55, Spain at 0.39, and Japan at 0.36. Research Implications - Efficiency of fiscal policy is dependent upon the reactions of economic agents. The priority of the government should focus on managing the future expectations of economic agents by implementing structural reforms in the labor market and pension system.

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Mohawesh, O. E. "Evaluation of evapotranspiration models for estimating daily reference evapotranspiration in arid and semiarid environments." Plant, Soil and Environment 57, No. 4 (April 21, 2011): 145–52. http://dx.doi.org/10.17221/240/2010-pse.

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Daily outputs from eight evapotranspiration models were tested against reference evapotranspiration (ETo) data computed by FAO56PM to assess the accuracy of each model in estimating ETo. Models were compared at eight stations across Jordan. Results show that Hargreaves modified models were the best in light of mean biased error (MBE), root mean square error (RMSE) and mean absolute error (MAE). The MBE, RMSE, and MAE values ranged from –1.47 to 0.81, 3.87 to 1.14 and 0.87 to 3.15 mm/day for HarM1, and from –1.45 to 0.89, 1.08 to 3.91, and 0.85 to 3.16 mm/day for HarM2, respectively, which would make it the best models in light of the MBE, RMSE and MAE ranging from –6.18 to 2.79, 6.90 to 1.08 and 4.74 to 0.85 mm/day for all models and stations. Comparisons were also made using three composite regions: countrywide, semiarid, and arid regions. In conclusion, local calibration is needed for the whole models or the linear regression can be used to calculate the ETo.

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Jee, Sang-Youn, and Kyung-Soo Kim. "Estimation of the Relationship between Inbound Tourism Income and Macroeconomic Growth using ARDL Model." Korean Business Education Review 37, no. 3 (April 30, 2022): 125–42. http://dx.doi.org/10.23839/kabe.2022.37.3.125.

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Žeželj, Branislav, Jovica Vasin, Jordana Ninkov, Zdravko Hojka, and Milorad Toković. "Application of the mathematical model 'Demand' for surface irrigation methods of arid and semi-arid regions." Savremena poljoprivredna tehnika 41, no. 4 (2015): 49–56. http://dx.doi.org/10.5937/savpoljteh1501049z.

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Salakpi, Edward E., Peter D. Hurley, James M. Muthoka, Adam B. Barrett, Andrew Bowell, Seb Oliver, and Pedram Rowhani. "Forecasting vegetation condition with a Bayesian auto-regressive distributed lags (BARDL) model." Natural Hazards and Earth System Sciences 22, no. 8 (August 23, 2022): 2703–23. http://dx.doi.org/10.5194/nhess-22-2703-2022.

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Abstract. Droughts form a large part of climate- or weather-related disasters reported globally. In Africa, pastoralists living in the arid and semi-arid lands (ASALs) are the worse affected. Prolonged dry spells that cause vegetation stress in these regions have resulted in the loss of income and livelihoods. To curb this, global initiatives like the Paris Agreement and the United Nations recognised the need to establish early warning systems (EWSs) to save lives and livelihoods. Existing EWSs use a combination of satellite earth observation (EO)-based biophysical indicators like the vegetation condition index (VCI) and socio-economic factors to measure and monitor droughts. Most of these EWSs rely on expert knowledge in estimating upcoming drought conditions without using forecast models. Recent research has shown that the use of robust algorithms like auto-regression, Gaussian processes, and artificial neural networks can provide very skilled models for forecasting vegetation condition at short- to medium-range lead times. However, to enable preparedness for early action, forecasts with a longer lead time are needed. In a previous paper, a Gaussian process model and an auto-regression model were used to forecast VCI in pastoral communities in Kenya. The objective of this research was to build on this work by developing an improved model that forecasts vegetation conditions at longer lead times. The premise of this research was that vegetation condition is controlled by factors like precipitation and soil moisture; thus, we used a Bayesian auto-regressive distributed lag (BARDL) modelling approach, which enabled us to include the effects of lagged information from precipitation and soil moisture to improve VCI forecasting. The results showed a ∼2-week gain in the forecast range compared to the univariate auto-regression model used as a baseline. The R2 scores for the Bayesian ARDL model were 0.94, 0.85, and 0.74, compared to the auto-regression model's R2 of 0.88, 0.77, and 0.65 for 6-, 8-, and 10-week lead time, respectively.

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Hwang, Yunmi, Kyeongmin Yong, and Jonghwa Kim. "Analysis of Factors Affecting the Reduction of Honey Production using the ARDL Model." Journal of the Korea Academia-Industrial cooperation Society 25, no. 1 (January 31, 2024): 393–402. http://dx.doi.org/10.5762/kais.2024.25.1.393.

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Ponziani, Regi Muzio. "Inflation forecasting using autoregressive distributed lag (ARDL) models." Jurnal Ekonomi & Studi Pembangunan 24, no. 2 (October 23, 2023): 316–30. http://dx.doi.org/10.18196/jesp.v24i2.17620.

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This study attempts to evaluate and compare the inflation-predicting performance of several ARDL models. Since there was no cointegration, the ARDL model does not employ an error correction term. Subsequently, model development showed that ARDL(2,2) should be used. Besides the formally developed model, some other more arbitrarily chosen ARDL models were also included, i.e., ARDL(1,1), ARDL(2,0), ARDL(1,0), ARDL(0,1), and ARDL(0,2). This research measures forecasting performance with inflation as the forecasting object. The duration of the monthly inflation statistics ranged from January 2011 to July 2022. The data were separated into two categories. The training data ranged between January 2011 and December 2021. After getting the appropriate parameters from the training data, the models generated projections from January 2022 to July 2022. The research determined that ARDL (1,0) was the most accurate inflation forecasting model, followed by ARDL (0,2) and formally constructed ARDL(2,2) finished in fourth place. This study suggests that the formal development of ARDL for forecasting purposes is unnecessary. Formal ARDL development is more appropriate for root cause analysis. In addition, the single autoregressive component indicates that most of the inflation value's information originated from the prior period. This suggests that the previous period's value is Indonesia's most significant predictor of inflation. The impact of greater period lags on inflation forecasting diminishes immediately.

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Hu, Caihong, Shenglian Guo, Lihua Xiong, and Dingzhi Peng. "A modified Xinanjiang model and its application in northern China." Hydrology Research 36, no. 2 (April 1, 2005): 175–92. http://dx.doi.org/10.2166/nh.2005.0013.

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The Xinanjiang model has been widely used in the humid regions in southern China as a basic tool for rainfall–runoff simulation, flood forecasting and water resources planning and management. However, its performance in the arid and semi-arid regions of northern China is usually not so good as in the humid regions. A modified Xinanjiang model, in which runoff generation in the watershed is based on both infiltration excess and saturation excess runoff mechanisms, is presented and discussed. Three different watersheds are selected for assessing and comparing the performance of the Xinanjiang model, the modified Xinanjiang model, the VIC model and the TOPMODEL in rainfall–runoff simulation. It is found that the modified Xinanjiang model performs better than the Xinanjiang model, and the models considering the Horton and Dunne runoff generation mechanisms are slightly better than those models considering the single runoff generation mechanism in semi-arid areas. It is suggested that the infiltration excess runoff mechanism should be included in rainfall–runoff models in arid and semi-arid regions.

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Gauvin-Bourdon, Phillipe, James King, and Liliana Perez. "Impacts of grazing on vegetation dynamics in a sediment transport complex model." Earth Surface Dynamics 9, no. 1 (February 2, 2021): 29–45. http://dx.doi.org/10.5194/esurf-9-29-2021.

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Abstract. Arid environments are characterized by the complex interaction between vegetation cover, surface soil properties, and the climate. The dynamic balance between these components makes arid environments highly susceptible to swift changes in vegetation cover and surface morphology in response to climate change. Furthermore, arid environments often support grazing activities, which influence other ecogeomorphic processes and alter the stability of vegetation cover in these environments. Despite growing knowledge and the parallel modeling advances to simulate the sediment transport, vegetation distribution, and grazing, in arid environments, relatively little progress has been accomplished on the interaction between all these components. Here we present an adaptation of an already established sediment transport–vegetation cellular automata model (Vegetation and Sediment TrAnsport or ViSTA) that represents landscape dynamics with an agent-based model (GrAM) representing the activity of grazers on the landscape. In this study, our resulting model, ViSTA_GrAM, is subjected to a series of 100-year-long tests that aim to highlight the capacity of the model to represent ecogeomorphic processes linked to vegetation composition, rainfall, wind speed, and grazing pressure. While these simulations do not allow us to evaluate the performance of the new model to reproduce realistic semi-arid environments, they present the capacity of the model to reproduce and explain major feedback complexities between grazers and the vegetation, in addition to providing insight on the vegetation and wind shear sensitivity of the original model. The simulations reinforce our current knowledge of the resilience of grass-based landscapes to foraging activities and highlight the need to identify growth response rates at the species level to fully understand the complexity of the interactions between individual components within arid environments. Overall, the ViSTA_GrAM model presents the foundation for a better assessment of semi-arid environment response to landscape management measures and a better understanding of the complex interactions shaping semi-arid landscapes.

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Shiroky, A. A., A. S. Isakov, and V. V. Novochadov. "The control model of arid plant communities." Journal of Physics: Conference Series 1864, no. 1 (May 1, 2021): 012053. http://dx.doi.org/10.1088/1742-6596/1864/1/012053.

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Milton, Suzanne J., and W. Roy Siegfried. "A Conceptual Model of Arid Rangeland Degradation." BioScience 44, no. 2 (February 1994): 70–76. http://dx.doi.org/10.2307/1312204.

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Lu, Weinan, Wenxin Liu, Mengyang Hou, Yuanjie Deng, Yue Deng, Boyang Zhou, and Kai Zhao. "Spatial–Temporal Evolution Characteristics and Influencing Factors of Agricultural Water Use Efficiency in Northwest China—Based on a Super-DEA Model and a Spatial Panel Econometric Model." Water 13, no. 5 (February 27, 2021): 632. http://dx.doi.org/10.3390/w13050632.

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Improving agricultural water use efficiency (AWUE) is an important way to solve the shortage of water resources in arid and semi-arid regions. This study used the Super-DEA (data envelopment analysis) to measure the AWUE of 52 cities in Northwest China from 2000 to 2018. Based on spatial and temporal perspectives, it applied Exploratory Spatial Data Analysis (ESDA) to explore the dynamic evolution and regional differences of AWUE. A spatial econometric model was then used to analyze the main factors that influence the AWUE in Northwest China. The results showed firstly that the overall AWUE in Northwest China from 2000 to 2018 presented a steady upward trend. However, only a few cities achieved effective agricultural water usage by 2018, and the differences among cities were obvious. Secondly, AWUE showed an obvious spatial autocorrelation in Northwest China and showed significant high–high and low–low agglomeration characteristics. Thirdly, economic growth, urbanization development, and effective irrigation have significant, positive effects on AWUE, while per capita water resource has a significant, negative influence. Finally, when improving the AWUE in arid and semi-arid regions, plans should be formulated according to local conditions. The results of this study can provide new ideas on the study of AWUE in arid and semi-arid regions and provide references for the formulation of regional agricultural water resource utilization policies as well.

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Hakim, Lukman, and Akmal Riza. "THIRD PARTY FUNDS AND WORKING CAPITAL FINANCING AT ISLAMIC BANKS IN INDONESIA: ARDL-ECM APPROACH." An-Nisbah: Jurnal Ekonomi Syariah 10, no. 2 (January 10, 2024): 135–48. http://dx.doi.org/10.21274/an.v10i2.8712.

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Abstrak: Penelitian ini bertujuan untuk menganalisis pengaruh dana pihak ketiga dan tingkat margin pembiayaan terhadap realisasi pembiayaan modal kerja yang disalurkan bank syariah pada sektor UMKM di Indonesia. Menggunakan data time series selama periode 2014.6-2018.9, model analisis yang digunakan adalah autoregressive distributed lag (ARDL). Penelitian mengungkapkan adanya hubungan kointegrasi jangka panjang antara realisasi pembiayaan dengan dana pihak ketiga dan tingkat margin pembiayaan. Dalam jangka panjang dan jangka pendek, dana pihak ketiga berpengaruh positif dan signifikan terhadap pembiayaan modal kerja. Selanjutnya, tingkat margin berpengaruh negatif dan signifikan dalam jangka pendek, tetapi tidak berpengaruh dalam jangka panjang. Kata kunci: Pembiayaan Modal Kerja, Dana Pihak Ketiga, tingkat Margin Pembiayaan, ARDL-ECM. Abstract: This research aims to analyze the influence of third-party funds and the yield rate of financing on the realization of working capital financing distributed by Islamic banks to the MSMEs sector in Indonesia. Using time series data for the period 2014M6-2018M9, the analysis model used is autoregressive distributed lag (ARDL). The research pointed out that there is a long-term cointegration relationship between the realization of Islamic financing with third-party funds and the yield rate. In the long term and short term, third-party funds have a positive and significant effect on working capital financing. Furthermore, the yield rate has a negative and significant effect in the short term but has no effect in the long term. Keywords: Working capital financing, Third-party funds, Yield rate of financing, ARDL-ECM.

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Lei, Xiaoni, Changchun Xu, Fang Liu, Lingling Song, Linlin Cao, and Nanji Suo. "Evaluation of CMIP6 Models and Multi-Model Ensemble for Extreme Precipitation over Arid Central Asia." Remote Sensing 15, no. 9 (April 30, 2023): 2376. http://dx.doi.org/10.3390/rs15092376.

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Simulated historical extreme precipitation is evaluated for Coupled Model Intercomparison Project Phase 6 (CMIP6) models using precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The indices of 33 Global Circulation Models (GCMs) are evaluated against corresponding indices with observations from the Global Climate Center Precipitation Dataset (GPCC V2020) over five sub-regions across Arid Central Asia (ACA), using the Taylor diagram, interannual variability skill score (IVS) and comprehensive rating index (MR). Moreover, we compare four multi-model ensemble approaches: arithmetic average multi-model ensemble (AMME), median multi-model ensemble (MME), pattern performance-based multi-model ensemble (MM-PERF) and independence weighted mean (IWM). The results show that CMIP6 models have a certain ability to simulate the spatial distribution of extreme precipitation in ACA and the best ability to simulate simple daily intensity (SDII), but it is difficult to capture the spatial bias of consecutive wet days (CWD). Almost all models represent different degrees of wet bias in the southern Xinjiang (SX). Most GCMs are generally able to capture extreme precipitation trends, but to reproduce the performance of interannual variability for heavy precipitation days (R10mm), SDII and CWD need to be improved. The four multi-model ensemble methods can reduce the internal system bias and variability within individual models and outperform individual models in capturing the spatial and temporal variability of extreme precipitation. However, significant uncertainties remain in the simulation of extreme precipitation indices in SX and Tianshan Mountain (TM). Comparatively, IWM simulations of extreme precipitation in the ACA and its sub-regions are more reliable. The results of this study can provide a reference for the application of GCMs in ACA and sub-regions and can also reduce the uncertainty and increase the reliability of future climate change projections through the optimal multi-model ensemble method.

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العوفي, حكيمة, and زوليخة بصدار. "سوق العمل والنمو الاقتصادي : نموذج ARDL = Labor Market and Economic Growth : ARDL Model." Revue Organisation et Travail 6, no. 2 (June 2017): 58–71. http://dx.doi.org/10.12816/0049430.

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Kamyab-Talesh, Forough, Behrouz Mostafazadeh-Fard, Majid Vazifedoust, Mohammad Shayannejad, and Maryam Navabian. "Salt Tolerance Analysis of Crops using the SWAP Model." Biosciences, Biotechnology Research Asia 14, no. 2 (June 25, 2017): 643–49. http://dx.doi.org/10.13005/bbra/2490.

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ABSTRACT: Soil and water salinities are major environmental factors limiting the productivity of agricultural lands especially in arid and semi arid regions. To determine salinity threshold values and slope of the yield decrements for crops of wheat, barley and maize, SWAP model was study for an arid region located in Semnan Province (52◦25' N 35◦11' E), central part of Iran with area of 35000 ha including 94 villages belonged to irrigation network of Garmsar district. The data collected from the above 94 villages for years 1998 to 2007 were used to calibrate and simulate yield of wheat, barley and maize using the SWAP model. The irrigation water salinities of 2, 4, 6 and 8 dS m-1 were used and yield reductions versus soil saturation extracts were evaluated and salinity threshold values and slope of the yield reductions were determined for each of the above crops. The results showed that the SWAP model predict crop yields with good accuracy and the threshold values and slope of the yield reductions are site dependent. These values should be determined for each area in order to be able to plan better irrigation scheduling for arid regions which have soil and irrigation water salinities problems.

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Kripfganz, Sebastian, and Daniel C. Schneider. "ardl: Estimating autoregressive distributed lag and equilibrium correction models." Stata Journal: Promoting communications on statistics and Stata 23, no. 4 (December 2023): 983–1019. http://dx.doi.org/10.1177/1536867x231212434.

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We present a command, ardl, for the estimation of autoregressive distributed lag (ARDL) models in a time-series context. The ardl command can be used to fit an ARDL model with the optimal number of autoregressive and distributed lags based on the Akaike or Bayesian (Schwarz) information criterion. The regression results can be displayed in the ARDL levels form or in the error-correction representation of the model. The latter separates long-run and short-run effects and is available in two different parameterizations of the long-run (cointegrating) relationship. The popular bounds-testing procedure for the existence of a long-run levels relationship is implemented as a postestimation feature. Comprehensive critical values and approximate p-values obtained from response-surface regressions facilitate statistical inference.

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Onour, Ibrahim A. "Effect of Carbon Dioxide Concentration on Cereal Yield in Sudan." Management and Economics Research Journal 5 (2019): 1. http://dx.doi.org/10.18639/merj.2019.740622.

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To estimate the long-term effect of carbon dioxide (CO2) emission on cereal yield in Sudan, we employed an autoregressive distributed lagged (ARDL) bound test for cointegration analysis. The ARDL results reveal evidence of cointegration between the dependent variable (cereals yield) and two independent variables (CO2 emission) and agricultural GDP. The estimation results of the error correction model indicate that change in CO2 has a positive and significant impact on the cereal yield in the long and short terms, as 1% increase in CO2 leads to a cereal yield increase by 3% in the short term and by 0.7% in the long term. This result adds two important findings to the existing literature: First, the positive impact of CO2 on cereal yield in Sudan supports previous research findings in other countries of warm and arid climates. Second, the effect of CO2 on cereal yield differs from short to long term, as our finding indicates that CO2 has a greater positive effect in the short term compared to that in the long term, implying that the effect of CO2 on cereal yields is not linear, as commonly perceived, but it decreases as time duration extends to longer periods. This may be due to the CO2 effect on global warming that emanates from cumulative CO2 concentration, which leaves a disproportionate impact on crops over time.

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Sun, Huaiwei, Yong Yang, Ruiying Wu, Dongwei Gui, Jie Xue, Yi Liu, and Dong Yan. "Improving Estimation of Cropland Evapotranspiration by the Bayesian Model Averaging Method with Surface Energy Balance Models." Atmosphere 10, no. 4 (April 8, 2019): 188. http://dx.doi.org/10.3390/atmos10040188.

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Evapotranspiration (ET) is one of the key components of the global hydrological cycle. Many models have been established to obtain an accurate estimation of ET, but the uncertainty of each model has not been satisfactorily addressed, and the weight determination in multi-model simulation methods remains unclear. In this study, the Bayesian model averaging (BMA) method was adopted to tackle this issue. We explored the combination of four surface energy balance (SEB) models (SEBAL, SSEB, S-SEBI and SEBS) with the BMA method by using Landsat 8 images over two study areas in China, the Huailai flux station (semiarid region) and the Sidaoqiao flux station (arid/semiarid region), and the data from two stations were used as validation for this method. The performances of SEB models and different BMA methods is revealed by three statistical parameters (i.e., the coefficient of determination (R2), root mean squared error (RMSE), and the Nash-Sutcliffe efficiency coefficient (NSE)). We found the best performing SEB model was SEBAL, with an R2 of 0.609 (0.672), RMSE of 1.345 (0.876) mm/day, and NSE of 0.407 (0.563) at Huailai (Sidaoqiao) station. Compared with the four individual SEB models, each of the BMA methods (fixed, posterior inclusion probability, or random) can provide a more accurate and reliable simulation result. Similarly, in Huailai (Sidaoqiao) station, the best performing BMA random model provided an R2 of 0.750 (0.796), RMSE of 0.902 (0.602) mm/day, and NSE of 0.746 (0.793). We conclude that the BMA method outperformed the four SEB models alone and obtained a more accurate prediction of ET in two cropland areas, which provides important guidance for water resource allocation and management in arid and semiarid regions.

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Guo, Zichen, Yuqiang Li, Xuyang Wang, Xiangwen Gong, Yun Chen, and Wenjie Cao. "Remote Sensing of Soil Organic Carbon at Regional Scale Based on Deep Learning: A Case Study of Agro-Pastoral Ecotone in Northern China." Remote Sensing 15, no. 15 (August 2, 2023): 3846. http://dx.doi.org/10.3390/rs15153846.

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The North China agro–pastoral zone is a large, ecologically fragile zone in the arid and semi-arid regions. Quantitative remote sensing inversion of soil organic carbon (SOC) in this region can facilitate understanding of the current status of degraded land restoration and provide data support for carbon cycling research in the region. Deep learning (DNN) for SOC inversion has been W.a hot topic over the past decade, but there have been few studies at the regional scale in the arid and semi-arid zones. In this study, a DNN model with five hidden layers and five skip connections was established using 644 spatially distributed SOC samples and Landsat 8 OLI imagery. The model was compared with the random forest algorithm in terms of generalization ability. The main conclusions were as follows: 1. The DNN algorithm can establish a high-precision SOC inversion model (R2 = 0.52, RMSE = 0.7), with 90% of errors concentrated in the range of −2.5 to 2.5 kg·C/m2; 2. the Boruta variable-screening algorithm can effectively improve the model accuracy of the random forest algorithm, but due to the DNN’s better ability to mine hidden information in the data, the improvement effect on the DNN model accuracy is limited; 3. the SOC samples in arid and semi-arid areas are highly positively skewed, with a significant impact on the modeling accuracy of DNN, and conversion is required to obtain a model with better generalization ability; and 4. in arid and semi-arid regions, SOC has a weak correlation with vegetation indices but a stronger correlation with temperature, elevation, and aridity. This study established a reliable deep learning model for SOC density in a large arid and semi-arid region, providing a reference and framework for the establishment of SOC inversion models in other regions.

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Shittu, Olanrewaju I., Raphael A. Yemitan, and OlaOluwa S. Yaya. "ON AUTOREGRESSIVE DISTRIBUTED LAG, COINTEGRATION AND ERROR CORRECTION MODEL: An Application to Some Nigeria Macroeconomic Variables." Australian Journal of Business and Management Research 02, no. 08 (September 11, 2012): 56–62. http://dx.doi.org/10.52283/nswrca.ajbmr.20120208a07.

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This paper reviews the use of the traditional ARDL and the ARDL approach to cointegration for the analysis of short-run dynamic and long run relationship when series are difference stationary (series can be integrated of different orders). The two models were used to estimate the short-run dynamics and the long run relationships between selected Nigeria’s macroeconomic series. The results compares favorably with the theory that the ARDL is equivalent to the short-run dynamics of the error correction model (the resultant model from the ARDL approach to cointegration).

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Wellman, Peter. "Australian corticolous myxomycetes: models of distribution and development." Australian Journal of Botany 67, no. 8 (2019): 617. http://dx.doi.org/10.1071/bt19155.

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This paper presents an integrated model of the variation over a continental landmass of myxomycetes, a single-celled organism in the phylum Amoebozoa. Bark samples were collected on long traverses across Australia, and cultivated in Petri dishes by the moist chamber technique to obtain large assemblages of common species. The results of this survey and previous surveys are consistent with there being four major myxomycete assemblages: Tropical, Northern Arid, Southern Arid and Temperate. Where mapped, these species assemblage regions are consistent with the Australian phytogeographical regions. The myxomycetes differ between arid and non-arid areas; the arid areas have slightly higher productivity per wetting event, with members of the Physarales and Liceales relatively important and the Stemonitidales, Trichiales and Cribrariales less important. When the bark samples are placed in a moist culture there is a myxomycete growth cycle and then the population declines to resting phases. The population increase during a growth phase can be modelled by a linear plot of log(abundance) against species rank, where abundance is total harvested spore volume of a species. The population decline appears to be linear from two weeks after watering, declining to negligible activity 4 weeks after watering.

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Ullah, Arif, Kashif Raza, Muhammad Nadeem, Usman Mehmood, Ephraim Bonah Agyekum, Mohamed F. Elnaggar, Ebenezer Agbozo, and Salah Kamel. "Does Globalization Cause Greenhouse Gas Emissions in Pakistan? A Promise to Enlighten the Value of Environmental Quality." International Journal of Environmental Research and Public Health 19, no. 14 (July 16, 2022): 8678. http://dx.doi.org/10.3390/ijerph19148678.

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Global environmental issues such as environmental degradation, climate change, and global warming have posed a threat to the global economy, including Pakistan. The primary source of these problems is greenhouse gas emissions. These emissions are the result of human activity. The objective of the study was to investigate the symmetric and asymmetric relationship between globalization and greenhouse gas emissions in Pakistan. The ARDL modern econometric techniques of the time series model were used. Firstly, the stationarity test favors the use of the ARDL model in this study. The BDS test result confirmed that the ARDL model has a non-linearity issue. As a result, the ARDL approach was used to test both the symmetric and asymmetric effect. The results of the asymmetric ARDL model are more robust and reliable than those of the symmetric ARDL model. According to the results of the symmetric ARDL, economic, social, and political globalization have a positive relationship with greenhouse gas emissions in both the short and long run. Furthermore, the long-run results of the asymmetric ARDL model show that positive and negative shocks of economic and political globalization have positive and negative shock effects on greenhouse gas emissions. In the long run, however, the positive shock of social globalization has a negative relationship with greenhouse gas emissions. According to the results of impulse response functions, economic globalization has a significantly more relationship with greenhouse gas emissions than social and political globalization. A policy should be developed that allows only the positive effects of globalization while prohibiting the negative effects of globalization.

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Matienko, Ludmila, Vladimir Binykov, Elena Mil, and Gennady Zaikov. "Role of Supramolecular Strucutres in Mechanisms of Catalytic Oxidation and Action of Ni(Fe)ARD Dioxygenases on Model Systems." Chemistry & Chemical Technology 14, no. 3 (September 22, 2020): 304–11. http://dx.doi.org/10.23939/chcht14.03.304.

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Zaretta, Bara, and Lenni Yovita. "HARGA SAHAM, NILAI TUKAR MATA UANG DAN TINGKAT SUKU BUNGA ACUAN DALAM MODEL AUTOREGRESSIVE DISTRIBUTED LAG (ARDL)." Jurnal Penelitan Ekonomi dan Bisnis 4, no. 1 (March 22, 2019): 9–22. http://dx.doi.org/10.33633/jpeb.v4i1.2318.

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Beberapa penelitian terdahulu telah banyak yang membuktikan adanya pengaruh antara nilai tukar Rupiah terhadap Dolar Amerika dan BI Rateterhadap IHSG. Namun dengan menggunakan pendekatan model Autoregressive Distributed Lag(ARDL) dalam penelitian ini lebih dalam lagi melihat dinamika hubungan jangka panjang maupun jangka pendek untuk variabel nilai tukar Rupiah terhadap Dolar Amerika, BI Ratedan IHSG. Untuk dapat menangkap dinamika tersebut diperlukan seleksi model ARDL terbaik dengan beberapa prosedur pengujian. Periode penelitian dimulai dari Juli 2005 sampai dengan Desember 2017, dimana dalam rentang waktu tersebut banyak terjadi pergolakan global yang memberikan dampak yang cukup besar terhadap Indonesia, salah satunya adalah pelemahan nilai tukar Rupiah terhadap Dolar Amerika. Mekanisme suku bunga acuan beberapa kali juga dipilih oleh Pemerintah Indonesia untuk menghadapi pergerakan nilai tukar Rupiah terhadap Dolar Amerika. Namun sebagaimana nilai tukar dan tingkat suku bunga acuan akan memberikan pengaruh kepada perekonomian secara keseluruhan dan terlebih lagi terhadap pasar modal yang juga merupakan indikator ekonomi suatu negara. Dalam penelitian ini, melalui model ARDL nilai tukar Rupiah terhadap Dolar Amerika, BI Ratedan IHSG terbukti memiliki kointegrasi jangka panjang atau bergerak bersama – sama dalam jangka panjang. Namun tidak hanya jangka panjang, ketiga variabel tersebut juga mempunyai dinamika hubungan jangka pendek yang mempunyai kecepatan penyesuaian menuju keseimbangan yang cukup tinggi perbulannya.Kata kunci : Nilai tukar, BI Rate, IHSG, Autoregressive Distributed Lag Model.

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Meng, Chunlei, and Wenlong Zhang. "Local and Regional Scale Evaluation of the Integrated Urban Land Model by Comparing with the Common Land Model." Advances in Meteorology 2019 (January 20, 2019): 1–11. http://dx.doi.org/10.1155/2019/4072497.

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Land surface evaporation is not only an important parameter in natural land surface modeling, but a crucial important parameter in urban hydrology modeling. A whole-layer soil evaporation scheme was developed in the integrated urban land model (IUM) to improve the soil evaporation simulation. The impervious surface evaporation (ISE) was used as a component of urban water balance equation. In this paper, the integrated urban land model was validated at one desert site and six urban road sites to emphasize the improvement in the evaporation simulations for arid and urban areas. A sensitivity analysis was implemented in seven basins to expand the utility of the whole layer soil evaporation scheme. For the urban road sites, the validation results indicate that imperious surface evaporation (ISE) plays a crucial role in road surface temperature (RST) simulations on rainy days. For the desert site, the validation results show that the inner layer evaporation is very important in arid regions. For the basins, the analysis results indicate that the relative monthly mean differences in the evapotranspiration (ET) between the simulations with (IUM) and without (Common Land Model (CoLM)) considering the inner layer evaporation range from −8% to 8%, which is proportional to the degree of dryness. In arid areas, especially deserts, the inner layer soil evaporation could not be neglected.

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Chen, B., H. C. Guo, G. H. Huang, I. Maqsood, N. Zhang, S. M. Wu, and Z. X. Zhang. "ASRWM: an arid/semiarid region water management model." Engineering Optimization 37, no. 6 (September 2005): 609–31. http://dx.doi.org/10.1080/03052150500132604.

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Habbane, A. Y., J. C. McVeigh, and S. O. I. Cabawe. "Solar radiation model for hot dry arid climates." Applied Energy 23, no. 4 (January 1986): 269–79. http://dx.doi.org/10.1016/0306-2619(86)90011-5.

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Mchirgui, Fadhila, Houda Ben Zarroug, and Nadhem Selmi. "Contagion of Financial Crisis: Evidence of ARDL Model." International Journal of Managerial Studies and Research 10, no. 5 (2022): 1–7. http://dx.doi.org/10.20431/2349-0349.1005001.

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Sharma, K. D., and J. S. R. Murthy. "A conceptual sediment transport model for arid regions." Journal of Arid Environments 33, no. 3 (July 1996): 281–90. http://dx.doi.org/10.1006/jare.1996.0065.

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Aden Mohamed, Abdisalan, and Salad Shire Mohamud. "Determinants of Economic Growth in Somalia: ARDL Model." International Journal of Scientific Research and Management 11, no. 01 (January 26, 2023): 4497–506. http://dx.doi.org/10.18535/ijsrm/v11i01.em10.

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Using an autoregressive distributed lag model (ARDL) and error correction technique, this paper investigates the short- and long-run relationships between exports, imports, and FDI on economic growth in Somalia. Secondary data was collected from the SESRIC website. The study spans the years 1995 to 2020. The result of the study revealed short- and long-term relationships between the variables. While FDI and exports have a negative long-term relationship with economic growth, imports have a positive long-term relationship. It also shows that FDI has a negative, short-run insignificant relationship with economic growth, whereas imports and exports have a significant, short-run relationship. Diagnostic tests were applied, and the results demonstrate that the model's validity for Somalia's economic growth is characterized by normality, the absence of serial correlation, and heteroscedasticity

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Wang, Haibo, Xin Li, Mingguo Ma, and Liying Geng. "Improving Estimation of Gross Primary Production in Dryland Ecosystems by a Model-Data Fusion Approach." Remote Sensing 11, no. 3 (January 22, 2019): 225. http://dx.doi.org/10.3390/rs11030225.

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Accurate and continuous monitoring of the production of arid ecosystems is of great importance for global and regional carbon cycle estimation. However, the magnitude of carbon sequestration in arid regions and its contribution to the global carbon cycle is poorly understood due to the worldwide paucity of measurements of carbon exchange in arid ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product provides worldwide high-frequency monitoring of terrestrial GPP. While there have been a large number of studies to validate the MODIS GPP product with ground-based measurements over a range of biome types. Few studies have comprehensively validated the performance of MODIS estimates in arid and semi-arid ecosystems, especially for the newly released Collection 6 GPP products, whose resolution have been improved from 1000 m to 500 m. Thus, this study examined the performance of MODIS-derived GPP by compared with eddy covariance (EC)-observed GPP at different timescales for the main ecosystems in arid and semi-arid regions of China. Meanwhile, we also improved the estimation of MODIS GPP by using in situ meteorological forcing data and optimization of biome-specific parameters with the Bayesian approach. Our results revealed that the current MOD17A2H GPP algorithm could, on the whole, capture the broad trends of GPP at eight-day time scales for the most investigated sites. However, GPP was underestimated in some ecosystems in the arid region, especially for the irrigated cropland and forest ecosystems (with R2 = 0.80, RMSE = 2.66 gC/m2/day and R2 = 0.53, RMSE = 2.12 gC/m2/day, respectively). At the eight-day time scale, the slope of the original MOD17A2H GPP relative to the EC-based GPP was only 0.49, which showed significant underestimation compared with tower-based GPP. However, after using in situ meteorological data to optimize the biome-based parameters of MODIS GPP algorithm, the model could explain 91% of the EC-observed GPP of the sites. Our study revealed that the current MODIS GPP model works well after improving the maximum light-use efficiency (εmax or LUEmax), as well as the temperature and water-constrained parameters of the main ecosystems in the arid region. Nevertheless, there are still large uncertainties surrounding GPP modelling in dryland ecosystems, especially for desert ecosystems. Further improvements in GPP simulation in dryland ecosystems are needed in future studies, for example, improvements of remote sensing products and the GPP estimation algorithm, implementation of data-driven methods, or physiology models.

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Saïdi, S., G. Gintzburger, L. Gazull, J. Wallace, and S. Christiansen. "A model for locating fodder shrub plantations sites in the Jordanian badiyah." Rangeland Journal 40, no. 5 (2018): 527. http://dx.doi.org/10.1071/rj17129.

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We developed a GIS desktop model to accurately locate and map prospective areas for sustainable establishment and production of Atriplex plantations and other fodder shrubs in the desert in the north-eastern Jordanian Badiyah. The aim is to provide a tool to assist managers, local communities and development projects in Mediterranean arid and semi-arid rangelands. The model uses freely available data and GIS layers of current land use, land cover, settlement location, soil information, and derivatives from a digital elevation model to provide critical locations of drainage lines and to calculate Areas of Accumulated Water from concentrated runoff. The model identified, accurately located and mapped ~4500 ha (1.44% of the test zone) as technically appropriate for potential shrub plantations sites. The final site map must be field-checked and validated with the local communities and authorities. Our model has potential for wide application over arid and semi-arid Mediterranean rangelands from Morocco to Pakistan, with local adjustment of our parameters and rules. The model considerably reduces the risk and costs of fodder plantation establishment operations, thus increasing the feasibility of efforts to maximise fodder shrub establishment, survival and production.

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Zheng, Jian Long, Can Qiang Mai, and Jun Hui Zhang. "A Mathematical Model for Subgrade Soil Water-Vapor Migration." Applied Mechanics and Materials 477-478 (December 2013): 604–9. http://dx.doi.org/10.4028/www.scientific.net/amm.477-478.604.

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In arid and semi-arid areas, water vapor transfer in non-saturated soil is usually more significant. Based on the existing theories such as soil mechanics and fluid mechanic, as well as the features on water vapor transfer in non-saturated soil, a formula to calculate the saturated water vapor pressure in soil void by taking the matrix suction and temperature into account was got, and a mathematical model for the moisture migration with time was deduced which reveals that a water-vapor migration phenomenon is uneven temperature distribution and uneven distribution moisture alone or in combination manifestations.

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聂, 景春. "An Adaptive Fuzzy Autoregressive Distributed Lag Time Series Based on Semi-Parametric Model." Operations Research and Fuzziology 14, no. 01 (2024): 938–46. http://dx.doi.org/10.12677/orf.2024.141087.

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Liu, Zhihong, Donghua Chen, Saisai Liu, Wutao Feng, Fengbing Lai, Hu Li, Chen Zou, Naiming Zhang, and Mei Zan. "Research on Vegetation Cover Changes in Arid and Semi-Arid Region Based on a Spatio-Temporal Fusion Model." Forests 13, no. 12 (December 4, 2022): 2066. http://dx.doi.org/10.3390/f13122066.

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Vegetation dynamics in arid and semi-arid regions have an important impact on carbon cycle, water cycle, and energy exchange at local, regional, and global scales. Therefore, it is of great significance for scientists to grasp the changes of vegetation cover in arid and semi-arid regions timely and accurately. Based on this, the applicability of ESTARFM model in the complex terrain area of arid and semi-arid Xinjiang was explored using Landsat and MODIS data fusion, and the overall change characteristics of vegetation cover (FVC) and the distribution and change patterns of different terrains in the study area in the past 15 years were analyzed by combining the dimidiate pixel model, unary linear regression and digital elevation model. The results show that: (1) the NDVI data fused by ESTARFM Model has high consistency with the real NDVI data, and it can be used for subsequent FVC estimation. (2) From 2006 to 2020, the inter FVC was at a high level as a whole, and the average annual FVC showed a weak increasing trend in fluctuation; there are obvious differences in spatial distribution, which is characterized by high distribution in the north and low in the south. (3) The improved area of vegetation cover in the study area is greater than the degraded area, accounting for 52.3% and 47.7% respectively; (4) In the elevation range of 2000 to 3500 m, the FVC showed a slight degradation trend on 25° to 45° slopes and south and southeast slopes, and the rest showed a slight improvement trend. ESTARFM-based model enables monitoring of vegetation cover changes in complex terrain areas of the arid and semi-arid regions in Xinjiang over a long time series. The overall FVC level in the study area is high, and there both are serious degradation and improvement phenomena.

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Jin, Hengxu, Xiaoping Rui, and Xiaoyan Li. "Analysing the Performance of Four Hydrological Models in a Chinese Arid and Semi-Arid Catchment." Sustainability 14, no. 6 (March 21, 2022): 3677. http://dx.doi.org/10.3390/su14063677.

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Frequent flood hazards in the Raoyang River Basin in western Liaoning, China, have posed serious threats to people’s lives and property. In an effort to study the simulation efficiencies of hydrological models in this arid and semi-arid catchment, this study examined the performance of the Xin’anjiang model, the Liaoning unsaturated model, and the DHF model in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China. Additionally, this paper proposed an improved DHF model, which considers the impoundment and regulation of small- and medium-sized reservoirs in the upper reaches of the basin. The flood simulation results demonstrated that the Xin’anjiang model was difficult to apply in this area because the average value of its Nash–Sutcliffe efficiency (NSE) was as low as 0.31. Meanwhile, the simulation efficiencies of the Liaoning unsaturated model and the DHF model were higher than that of the Xin’anjiang model, but the relative error of flood peak discharge and runoff depth for most floods were still high and could not meet the actual forecast requirements by the Reservoir Administration Bureau of Liaoning Province. Overall, the improved DHF model showed the best efficiency, and the mean value of the NSE reached 0.79. Therefore, the improved DHF model has good applicability in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China.

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Handoyo, Samingun, Ying-Ping Chen, Tiara Mawidha Shelvi, and Heni Kusdarwati. "Modeling Vector Autoregressive and Autoregressive Distributed Lag of the Beef and Chicken Meat Prices during the Covid-19 Pandemic in Indonesia." Journal of Hunan University Natural Sciences 49, no. 3 (March 28, 2022): 220–31. http://dx.doi.org/10.55463/issn.1674-2974.49.3.25.

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The impact of the COVID-19 pandemic has spread to all aspects of life. Modeling the price of beef and chicken meat is very important for the government to avoid extreme fluctuations of both commodities in the prices so that society's purchasing power can be maintained. This study has several objectives, namely building VAR and ARDL models from multiple time series data (beef and chicken meat prices), conducting variable selection with forwarding subset selection on input lag in the ARDL model, and measuring the performance of the VAR and ARDL models on the both of beef and chicken meat prices based on the value of RMSE, MAE, and R_square both in the training and testing set. The novelty in this study is to propose an identification method for the lag inputs of the ARDL model based on the criteria of both the Alkaide Information criteria (AIC) value and the adjusted R square value by visualizing both criteria for all possible amounts of lag inputs. The results of the identification of the VAR model structure using the conventional method in time series modeling are yielded the different lag inputs that are compared to the ARDL model structure with lag inputs identified by using the proposed method. The ARDL model of the beef and chicken meat prices has better performance than the VAR model both on training and testing sets. In addition, the resulting VAR model also clearly shows the occurrence of overfitting problems.

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Ganz, Tomas. "Preventive Therapy of Emphysema: Lessons from the Elastase Model." American Review of Respiratory Disease 135, no. 4 (April 1987): 984. http://dx.doi.org/10.1164/arrd.1987.135.4.984a.

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Zamani, Hossein, and Ommolbanin Bazrafshan. "Modeling monthly rainfall data using zero-adjusted models in the semi-arid, arid and extra-arid regions." Meteorology and Atmospheric Physics 132, no. 2 (July 20, 2019): 239–53. http://dx.doi.org/10.1007/s00703-019-00685-6.

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Journal articles on the topic 'ARLD model'

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