Abstract
An optoelectronic system for fog detection and visibility technique is presented .The idea of this research is based on the measurement of the atmospheric visibility by using an infrared beam emitter from LED diode. The optical scattering is used as a method to calculate the visibility. This method is applied at forward scattering within a foggy atmosphere, which is modern and has great importance for measuring visibility in seaports, airports, public roads and highways. In this paper we focus on the description of the system, principles of its operation and some results of field tests.
Keywords: fog sensor, visibility sensor, backscattering, forward scattering.
The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
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