accurate estimation of evaporation is important for design, planning and operation of water systems. in arid zones where water resources are scarce, the estimation of this loss becomes more interesting in the planning and management of irrigation practices. this paper investigates the ability of artificial neural networks (anns) technique to improve the accuracy of daily evaporation estimation....

In this paper, we consider spiking neural P systems with antispikes. Because of the use of two types of objects, the system can encode the binary digits in a natural way and hence represent the formal models more efficiently and naturally than the standard SN P systems. This work deals with the computing power of spiking neural P system with anti-spikes. It is demonstrated that, as transducers,...

The aim of this paper is to discuss the possible role of neural nets for decision support. The discussion will be conducted along two connected lines. The rst line regards the possibilities to solve combinatorial optimization problems with multi-layered perceptrons. Particular attention is paid to the required complexity of such neural nets. The second line regards the use of neural nets as a k...

Despite the great potential of deep neural networks (DNNs), they require massive weights and huge computational resources, creating a vast gap when deploying artificial intelligence at low-cost edge devices. Current lightweight DNNs, achieved by high-dimensional space pre-training post-compression, present challenges covering resources deficit, making tiny hard to be implemented. Here we report...

Graph Neural Networks (GNNs) have exploded onto the machine learning scene in recent years owing to their capability model and learn from graph-structured data. Such an ability has strong implications a wide variety of fields whose data are inherently relational, for which conventional neural networks do not perform well. Indeed, as reviews can attest, research area GNNs grown rapidly lead deve...