Among the existing GDP forecasting methods, time series and regression model are two most commonly used methods. However, traditional macroeconomic models unable to accurately achieve optimal forecasts of highly complex nonlinear dynamic systems due influence multiple confounding factors. In order solve above problems, a economic based on an improved RBF neural network is proposed. First, main ...

Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It categorized as brain due to its impact on brain. Various methods such electroencephalography (EEG), functional magnetic resonance imaging (FMRI), magnetoencephalography (MEG) can capture activities structures. EEG signals provide valuable insights into neurological disord...

Reconfigurable system on chip is well known for its flexibility for high performance embedded systems. The hardware/software (HW/SW) partitioning is the most important phase during the design of reconfigurable system on chip. A great many different algorithms have been adopted for solving the hardware/software partitioning problem. Shuffled Frog Leaping Algorithm (SFLA) is popular for its simpl...

The dynamic weapon target assignment (DWTA) problem is of great significance in modern air combat. However, DWTA a highly complex constrained multi-objective combinatorial optimization problem. An improved elitist non-dominated sorting genetic algorithm-II (NSGA-II) called the shuffled frog leaping algorithm (NSFLA) proposed to maximize damage enemy targets and minimize self-threat combat const...

In this paper, a new algorithm which is the result of the combination of cellular learning automata and frog leap algorithm (SFLA) is proposed for optimization in continuous, static environments.At the proposed algorithm, each memeplex of frogs is placed in a cell of cellular learning automata. Learning automata in each cell acts as the brain of memeplex, and will determine the strategy of moti...