Past research on the process of extinguishing a fire typically used a traditional linear water jet falling point model and the results ignored external factors, such as environmental conditions and the status of the fire engine, even though the water jet falling point location prediction was often associated with these parameters and showed a nonlinear relationship. This paper constructed a BP (Back Propagation) neural network model. The fire gun nozzle characteristics were included as model inputs, and the water discharge point coordinates were the model outputs; thus, the model could precisely predict the water discharge point with small error and high precision to determine an accurate firing position and allow for the timely adjustment of the spray gun. To improve the slow convergence and local optimality problems of the BP neural network (BPNN), this paper further used a genetic algorithm to optimize the BPNN (GA-BPNN). The BPNN can be used to optimize the weights in the network to train them for global optimization. A genetic algorithm was introduced into the neural network approach, and the water jet landing prediction model was further improved. The simulation results showed that the prediction accuracy of the GA-BP model was better than that of the BPNN alone. The established model can accurately predict the location of the water jet, making the prediction results more useful for firefighters.
The fuel consumption measure is inaccurate and no real-time with the three-scale mete in the special vehicles, so the real-time fuel measurement system is developed with the technologies of ultrasonic sensing, single-chip microcontroller, BDS positioning and wireless communication. An ultrasonic oil level sensor is stuck on the bottom of each tank to detect the remaining oil of tanks accurately. It can avoid destroying the existing equipment structure. BDS positioning module is applied to monitor the location of vehicle. This technology is China complete autonomy. The special wireless transmission module and special network node are set up for transmitting the data of fuel consumption and position. It can guarantee the transmission secure and confidential. And a fuel consumption detection algorithm is studied with BDS measuring distance. The prototype is tested in four different road conditions. The error rate of oil detection on a highway with good conditions is 3.92%. And the measured fuel consumption value is close to the manufacturer’s nominal value. The analysis of experimental data shows that the design of the detection system is reasonable and the fuel consumption detection algorithm is correct and reliable, and real-time fuel detection and positioning for the special vehicles can be realized.
Few studies have been conducted on the forest spatial channel matrix, most of which were conducted by experts and scholars in the field of communications. The mature cellular network channel coding matrix was ''transplanted'' to the vegetation-covered space, and the effects of the various vegetation dielectric constants, the forest canopy density and other objective factors on the traditional cellular channel were ignored. To overcome this problem, this paper built a relay network that is suitable for forest environments. This network was an effective complement to the existing cellular communication network for expanding the coverage of signals in the forest. On this basis, this paper analysed the multi-antenna relay transmission protocol and proposed an additional spatial channel matching (mapping) matrix between the forward and backward filters. This matrix was designed to consider the effect of the complex forest environment on the channel to reduce the relaying noise power. Then, under the forest cellular relay network topology, a spatial channel matrix structure (based on unitary matrix) that is suitable for the forest environment is proposed. This matrix can be incorporated into various relay protocols and considers the source node preprocessing operation and the destination node equalizer. The forest relay cooperative network that is proposed in this paper can effectively expand the coverage of signals in forest areas; however, due to the inherent limitations of the relay network, many problems will be encountered in practical applications. For example, the precoding scheme that is based on phase correction requires the terminal node to feed the phase correction factor back to the forest base station node; however, the system performance is substantially affected by the feedback accuracy and the arrival delay difference. Due to the uncertain rank of the integrated channel in the forest base station precoding scheme, it was necessary to adapt to a variety of antenna ports, which rendered the design of the precoding codebook highly difficult. In addition, when the number of transmission layers was greater than 1, the local precoding scheme also encountered the problem of inter-layer interference (ILI). Based on a detailed analysis of the shortcomings of the previous scheme and the strategy of partial coherence transmission, this paper proposes an improved algorithm of incoherent joint transmission technology and an improved precoding scheme that are suitable for forest relay systems. The signal that is transmitted by the relay node and the feedback signal is corrected via layer exchange between cells and via phase correction. By changing the layer's exchange information and phase information, it can be adapted to various forest environments, such as artificial forests, natural forests, and virgin forests. Finally, the outage probability is considered as a performance indicator in the simulation of the forest environment wireless relay system. The theoretical analysis and simulation results demonstrate the s...
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