Photovoltaic power is now a major green energy resource, and its generated power can be directly connected to the power grid. However, the stability of power grid may be affected by the random and intermittent characteristics of photovoltaic power. In order to solve this problem, a forecasting model based on the deep belief nets is proposed. First, affecting factors of photovoltaic power generation are studied, including solar radiation intensity, air temperature, relative humidity, and wind speed. Based on the correlation coefficient between output power and each factor, the most influential factors can be determined and used as inputs of the proposed forecasting model for training process. Second, the forecasting model is then established and applied to predict the photovoltaic output powers for 2 weeks in summer and winter, respectively. The mean absolute percentage error, mean squared error, and Theil's inequality coefficient are used to evaluate the performance efficiency between the proposed deep belief net model and back propagation neural network model. The performance outcomes reveal that the proposed deep belief net model can improve the prediction errors with rapid convergence significantly, better than the back propagation model.

With the development of the economy and society, environmental pollution and resource waste problems are emerging, especially in agricultural production, and the adoption of ecological agricultural technologies is a prerequisite to alleviate ecological pressure. Based on the Technology Acceptance Model—Theory of Planned Behavior (TAM-TPB) and using research data from Hubei, Hunan, and Anhui provinces, this paper empirically analyzes the factors influencing farmers’ intention to adopt rice and shrimp crop technologies using the PLS-SEM method. The configuration path of high technology intention was further investigated by the fsQCA method. The results showed that: 1) farmers’ intention to adopt rice-shrimp crop technology was mainly positively influenced by behavioral attitude, subjective norm, perceived behavioral control, behavioral attitude; 2) Perceived usefulness and perceived ease of use had a direct effect on farmers’ intention to adopt and an indirect effect with behavioral attitude as a mediating variable, while perceived ease of use had a positive effect and perceived usefulness did not. In doing so, four configuration paths of high technology acceptance intention were obtained. Given this, this paper makes relevant suggestions, suggesting that the relevant departments focus on the comprehensive benefits of rice-shrimp crop technology; agricultural technology departments provide technical assistance to farmers, and village committees organize regular inter-farmer exchanges.

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In order to realize long-distance, long-term and on-line cable tension monitoring of suspension bridges, a novel sensor has been designed based on Fiber Bragg Grating (FBG) sensing technique, which comprises of fixtures of the sensor as well as FBG, micro-spring and epoxy resin made large gauge sensing element. Further, following the calibration test for the designed FBG sensor, research on the calibrated sensor for monitoring the cable tension was carried out, whose result shows that, featured by the simplicity of operation and the accurate monitoring data, the designed FBG sensor is capable of monitoring the cable tension of built suspension bridges.

The main object of this paper is to examine the current situation of ICT (Information Communication Technology)