Benchmark estimates for aboveground litterfall data derived from ecosystem models

a new approach to credibility premium for zero-inflated poisson models for panel data

هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...

Discovering Ecosystem Models from Time-Series Data

Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery

Maps of forest biomass are important tools for managing natural resources and reporting terrestrial carbon stocks. Using the San Juan National Forest in Southwest Colorado as a case study, we evaluate regional biomass maps created using physical variables, spectral vegetation indices, and image textural analysis on Landsat TM imagery. We investigate eight gray level co-occurrence matrix based t...

Benchmark Forecasting in Data Envelopment Analysis for Decision Making Units

Although DEA is a powerful method in evaluating DMUs, it does have some limitations. One of the limitations of this method is the result of the evaluation is based on previously data and the results are not proper for forecasting the future changes. So For this purpose, we design feedback loops for forecasting inputs and outputs through system dynamics and simulation. Then we use DEA model to f...

Seasonal variation in ecosystem parameters derived from FLUXNET data

Seasonal variation in ecosystem parameters derived from FLUXNET data M. Groenendijk, M. K. van der Molen, and A. J. Dolman VU University Amsterdam, Faculty of Earth and Life Sciences, Department of Hydrology and Geo-environmental Sciences, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands Received: 28 January 2009 – Accepted: 1 March 2009 – Published: 11 March 2009 Correspondence to: M. Gro...