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Vanessa de Arruda Souza, Débora Regina Roberti, Anderson Luis Ruhoff, Tamíres Zimmer, Daniela Santini Adamatti, Luis Gustavo G. de Gonçalves, Marcelo Bortoluzzi Diaz, Rita de Cássia Marques Alves and Osvaldo L. L. de Moraes
Evapotranspiration (ET) is an important component of the hydrological cycle. Understanding the ET process has become of fundamental importance given the scenario of global change and increasing water use, especially in the agricultural sector. Determinin...
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Ahmed Skhiri, Ali Ferhi, Anis Bousselmi, Slaheddine Khlifi and Mohamed A. Mattar
A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term ave...
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Christian Haas, Philipp Klaus Thumser, Michael Hellmair, Tyler J. Pilger and Martin Schletterer
With the globally increasing awareness regarding the interconnectivity between freshwater ecosystems, projects for re-establishing connectivity with fishways as well as stock management are increasing. To ensure the quality and impact of such projects an...
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Guilherme Ramos Milis, Christophe Gay, Marie-Cécile Alvarez-Herault and Raphaël Caire
In the context of increasingly necessary energy transition, the precise modeling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campa...
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José Francisco Lima, Fernanda Catarina Pereira, Arminda Manuela Gonçalves and Marco Costa
Linear models, seasonal autoregressive integrated moving average (SARIMA) models, and state-space models have been widely adopted to model and forecast economic data. While modeling using linear models and SARIMA models is well established in the literat...
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Fátima Trindade Neves, Manuela Aparicio and Miguel de Castro Neto
In the rapidly evolving landscape of urban development, where smart cities increasingly rely on artificial intelligence (AI) solutions to address complex challenges, using AI to accurately predict real estate prices becomes a multifaceted and crucial tas...
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Tsonyo M. Pavkov, Valentin G. Kabadzhov, Ivan K. Ivanov and Stoil I. Ivanov
In this paper, we provide a detailed local convergence analysis of a one-parameter family of iteration methods for the simultaneous approximation of polynomial zeros due to Ivanov (Numer. Algor. 75(4): 1193?1204, 2017). Thus, we obtain two local converge...
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Apolinario Lujano, Miguel Sanchez-Delgado and Efrain Lujano
The FAO 56 Penman?Monteith equation (PM) is considered the most accurate method for estimating reference evapotranspiration (ETo). However, PM requires a large amount of data that is not always available. Thus, the objective of this study is to improve t...
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Alvaro Arroyo Cebeira and Mariano Asensio Vicente
In this paper, we propose a nonlinear tracking solution for maneuvering aerial targets based on an adaptive interacting multiple model (IMM) framework and unscented Kalman filters (UKFs), termed as AIMM-UKF. The purpose is to obtain more accurate estimat...
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Claudia Sangüesa, Roberto Pizarro, Ben Ingram, Alfredo Ibáñez, Diego Rivera, Pablo García-Chevesich, Juan Pino, Felipe Pérez, Francisco Balocchi and Francisco Peña
Estimating intensity-duration-frequency (IDF) curves requires local historical information of precipitation intensity. When such information is unavailable, as in areas without rain gauges, it is necessary to consider other methods to estimate curve para...
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