On The Effect of Preprocessing Techniques For Evapotranspiration Estimation Using Soft Computing Methods

Implementing a reliable computational model for predicting the reference evapotranspiration (ET0) process is essential for several agricultural and hydrological applications, especially for the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this research, two artificial intelligence (AI) models, artificial neural network (ANN) and model tree (MT), were investigated for modelling ET0. To validate model performance, five climatic stations such as Urmia, Mahabad, Takab, Khoy, and sardasht in West Azerbaijan Province of Iran. In the next step and to improve the model's accuracy, a novel preprocessing algorithm, ensemble empirical mode decomposition (EEMD), was coupled with those AI models to remove the trends or noise in the time series dataset. The extracted results indicated that the EEMD-MT model for all five stations outperformed other standalone and hybrid models.

Application of soft computing methods in robotic grasping: A state-of-the-art survey

Robotic grasping has become one of the most important domains of robotics research over the past few decades due to its wide range of applications in industrial automation. The model of grasping objects by robot hand depends on a good number of factors, such as type and size of the object, the morphology of object, type of hand, degree of freedom, etc. Thus, the model sometimes becomes mathematically intractable. With the progress in computational capability, soft computing methods have found a way to address the challenges faced by traditional methods while dealing with the robotic grasping problem. This article aims to summarize the outcome of a systematic study in the field of application of soft computing methods in robotic grasping and manipulation. The key processes of robotic grasping where soft computing methods are applied are identified, and research contributions of all processes are analyzed. This review presents a state-of-the-art survey and attempts to find the research gaps in the area of soft computing applications to address the robotic grasping problem.

Soft Computing for Decision-Making in Fuzzy Environments: A Tribute to Professor Ioan Dzitac

This paper is dedicated to Professor Ioan Dzitac (1953–2021). Therefore, his life has been briefly presented as well as a comprehensive overview of his major contributions in the domain of soft computing methods in a fuzzy environment. This paper is part of a special reverential volume, dedicated to the Centenary of the Birth of Lotfi A. Zadeh, whom Ioan Dzitac considered to be is his mentor, and to whom he showed his gratitude many times and in innumerable ways, including by being the Guest Editor of this Special Issue. Professor Ioan Dzitac had many important achievements throughout his career: he was co-founder and Editor-in-Chief of an ISI Expanded quoted journal, International Journal of Computers Communications & Control; together with L.A. Zadeh, D. Tufis and F.G. Filip he edited the volume “From Natural Language to Soft Computing: New Paradigms in Artificial Intelligence”; his scientific interest focused on different sub-fields: fuzzy logic applications, soft computing in a fuzzy environment, artificial intelligence, learning platform, distributed systems in internet. He had the most important contributions in soft computing in a fuzzy environment. Some of them will be presented in this paper. Finally, some future trends are discussed.