Kisi O.,Canik Basari University |
Kilic Y.,Turkey Ministry of Transport
Theoretical and Applied Climatology | Year: 2015
The generalization ability of artificial neural networks (ANNs) and M5 model tree (M5Tree) in modeling reference evapotranspiration (ET0) is investigated in this study. Daily climatic data, average temperature, solar radiation, wind speed, and relative humidity from six different stations operated by California Irrigation Management Information System (CIMIS) located in two different regions of the USA were used in the applications. King-City Oasis Rd., Arroyo Seco, and Salinas North stations are located in San Joaquin region, and San Luis Obispo, Santa Monica, and Santa Barbara stations are located in the Southern region. In the first part of the study, the ANN and M5Tree models were used for estimating ET0 of six stations and results were compared with the empirical methods. The ANN and M5Tree models were found to be better than the empirical models. In the second part of the study, the ANN and M5Tree models obtained from one station were tested using the data from the other two stations for each region. ANN models performed better than the CIMIS Penman, Hargreaves, Ritchie, and Turc models in two stations while the M5Tree models generally showed better accuracy than the corresponding empirical models in all stations. In the third part of the study, the ANN and M5Tree models were calibrated using three stations located in San Joaquin region and tested using the data from the other three stations located in the Southern region. Four-input ANN and M5Tree models performed better than the CIMIS Penman in only one station while the two-input ANN models were found to be better than the Hargreaves, Ritchie, and Turc models in two stations. © 2015 Springer-Verlag Wien Source
Agency: Cordis | Branch: H2020 | Program: CSA | Phase: GALILEO-4-2014 | Award Amount: 1.93M | Year: 2015
The overall project concept consists of building capacity in the field of multi-modal applications, focussed mainly on aviation using EGNSS in different Eastern European and Mediterranean countries. These countries are located at boundaries of the EGNOS SOL coverage area with limited EGNSS experience; the projects will promote the development of multi-modal applications, building on the lessons learnt in previous European R&D activities. With relation to the calls objectives, the goal of BEYOND is threefold: - Promoting the use of EGNSS outside the EU in neighbouring countries and stimulating investments in EGNSS - Preparing these countries for an optimal adoption of EGNSS and thus contributing to the increase in knowledge of EGNSS outside the EU - Supporting networking between EU and non-EU players, from industry, institutions, research, academia, higher education and creating a basis for cooperation and business opportunities in EU neighbours; for aviation and other fields. The project is intended to achieve a critical mass of new EGNSS applications, including multi-modal and aviation, providing crucial financial support and increasing the visibility of EGNSS in the different countries involved in the project. The BEYOND project represents an important asset in supporting the GSA in the implementation of EGNSS applications in the wider Europe.