Membrane-type acoustic metamaterials (MAMs) have recently received widespread attention due to their good low-frequency sound-transmission-loss (STL) performance. A fast prediction method for the STL of rectangular membranes loaded with masses of arbitrary shapes and surface density values is proposed as a semi-analytical model for calculating the STL of membrane-type acoustic metamaterials. Through conformal mapping theory, the mass blocks of arbitrary shapes were transformed into regular shapes, which simplified the calculation model of acoustic propagation loss prediction, and the prediction results were verified by finite element simulations. The results show that the change in mass surface density was closely related to the size and frequency distribution of STL. The influence of the mass center on the STL and characteristic frequency of the film metamaterial is discussed.

When dealing with specific tasks, the hidden layer output matrix of an extreme learning machine (ELM) may change, largely due to the random assigned weight matrix of the input layer and the threshold matrix of the hidden layer, which sequentially leads to the corresponding change to output weights. The unstable fluctuations of the output weights increase the structural risk and the empirical risk of ELM. This paper proposed a fuzzy adaptive particle swarm optimization (PSO) algorithm to solve this problem, which could nonlinearly control the inertia factor during the iteration by fuzzy control. Based on the fuzzy adaptive PSO-ELM algorithm, a sound quality prediction model was developed. The prediction results of this model were compared with the other three sound quality prediction models. The results showed that the fuzzy adaptive PSO-ELM model was more precise. In addition, in comparison with two other adaptive inertia factor algorithms, the fuzzy adaptive PSO-ELM model was the fastest model to reach goal accuracy.

The hinge and suction dredger is widely used in the construction field such as in river and lake management, water dredging, and port infrastructure projects, etc. With the continuous development of modern dredging technology, the traditional hinge and suction dredger cannot adapt to the complex environment during the construction process and there are problems such as large energy consumption and over-excavation and leakage excavation. In this paper, a double cutter dredger was designed that has a wider adaptability to water than a single cutter dredger. At the same time, based on the principle of passive adaptive control, the working parameters of the control system were calculated and determined, and an adaptive control algorithm was proposed to determine the water environment by using the current difference between the two cutters. Finally, the feasibility of the structure and algorithm was verified by experiments. The efficiency of cutter suction dredger was improved, and the energy consumption was reduced by 9–25% in the ideal state.