With the rapid development of emerging technologies, intelligent agriculture is incorporating techniques such as the Internet of Things, big data, cloud computing, artificial intelligence, blockchains, and fifth-generation mobile communication to improve work efficiency, prevent various disasters, and change the sales mode of agricultural products. Ornamental fishery is a part of agriculture and accounts for a significant proportion of commercial trade. This paper introduces image processing technology to help ornamental fisheries calculate the number of shrimps quickly. To solve the problem of overlapping live shrimps when counting, K-means unsupervised machine learning is adopted to determine the area of one shrimp. In addition, the proposed method using unsupervised machine learning is able to count different types of shrimp with high accuracy, such as crystal red shrimps, fire red shrimps, and Takashi Amano shrimps.We also analyze two background subtraction techniques, hue/saturation/value (HSV) histogrambased detection and Sobel edge detection, to compare the accuracy and calculation time of this application.

This paper introduces an optimal model named Self-Organizing Type-2 Recurrent Wavelet Fuzzy Brain Emotional Learning Network controller (SET2RWFBELNC) with self-evolving algorithm to gain optimal structure from zero initial rule, which merges Interval Type-2 Recurrent Wavelet Fuzzy System and Brain Emotional Learning Network(BELN). As an ideal controller, SET2RWFBELNC not only solves the problem of less information between master and slave systems, but also reduces the influence of external disturbance on synchronization of chaotic systems. Consequently, one model-free adaptive sliding mode controller based on SET2RWFBELNC, sliding model theory, and the asymptotic stability of the synchronization error is realized by robust compensation, in which the strong compensation used for the compensation of the network error. Besides, the Lyapunov function improves the stability of the model. Finally, simulation results of the chaotic system presented in this paper show the superiority of this method. INDEX TERMS Type-2 recurrent wavelet fuzzy system, Sliding mode control, Brain Emotion Learning Network, Model-free adaptive control,Chaotic system.