To solve problems of low positioning accuracy and long time-consuming in indoor visible light three-dimensional positioning system, a visible light three-dimensional positioning method based on the improved hybrid bat algorithm (IHBA) is proposed in this paper. Firstly, some beacon points are set at the beginning of the IHBA to reduce the number of iterations. Secondly, weight coefficient is defined to improve positioning accuracy when the fitness function is constructed. Thirdly, aiming at controlling the search speed reasonably, an adaptive search factor is introduced while the bat individual update formula is designed. Finally, the chaotic perturbation operation is used to avoid the algorithm falling into local optimum. In indoor simulation environment, the size of which is 5m×5m×3m, the average positioning error of the IHBA is 1.16cm and the positioning time is 1.85s. To verify the actual effectiveness of IHBA, a receiver is placed in the experimental environment, the size of which is 1.5m×1.2m×2m. Through the optical power detected by the receiver, the processor calculate its coordinates with IHBA. The average positioning error of the IHBA is 3.64cm and the positioning time is 0.89s. In this paper, the three-dimensional positioning system based on the IHBA algorithm can achieve high-precision and low-time positioning, and it has practical application value in existing indoor positioning methods.
The problem of a scarce consideration of screw pump well pump diagram graphic information affects the diagnosis technology promotion and utilization to some extent. The method, through which the shape features in pump diagram graphic state and parameter information been directly extracted, and then a method based on Mathematical morphology is also presented. Mathematical morphology filters of open-close operator to realize graphics edge texture feature extraction. After feature digitized, using a probabilistic neural network to identify fault. The practical application shows the classification accuracy rate is above 90%.
Owing to the growing volumes of mobile telecommunications customers, Internet websites, and digital services, there are more and more big data styles and types around the world. With the help of big data technology with high semantic information, this paper focuses on exploring the value and corresponding application of big data in finance. By comparing with the existing methods in terms of search speed and data volume, we can effectively see the effectiveness and superiority of the algorithm proposed in this paper. Furthermore, the algorithm proposed in this paper can provide some reference ideas for the follow-up-related research work.
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