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Migration time prediction and assessment of toxic fumes under forced ventilation in underground mines

Underground Space 2024年第5期18卷 273-294页

作者： Jinrui Zhang Tingting Zhang Chuanqi Li School of Resources&Civil Engineering Northeastern UniversityShenyang 110819China Laboratory 3SR CNRS UMR 5521Grenoble Alpes UniversityGrenoble 38000France

This study aims to predict the migration time of toxic fumes induced by excavation blasting in underground *** reduce numerical simulation time and optimize ventilation design,several back propagation neural network(BPNN)models optimized by honey badger algorithm(HBA)with four chaos mapping(CM)functions(i.e.,Chebyshev(Che)map,Circle(Cir)map,Logistic(Log)map,and Piecewise(Pie)map)are developed to predict the migration time.125 simulations by the computational fluid dynamics(CFD)method are used to train and test the developed *** determination coefficient(R2),the variance accounted for(VAF),the Willmott’s index(WI),the root mean square error(RMSE),the mean absolute percentage error(MAPE),and the sum of squares error(SSE)are utilized to evaluate the model *** evaluation results indicate that the CirHBA-BPNN model has achieved the most satisfactory performance by reaching the highest values of R2(0.9945),WI(0.9986),VAF(99.4811%),and the lowest values of RMSE(15.7600),MAPE(0.0343)and SSE(6209.4),*** wind velocity in roadway(Wv)is the most important feature for predicting the migration time of toxic ***,the intrinsic response characteristic of the optimal model is implemented to enhance the model interpretability and provide reference for the relationship between features and migration time of toxic fumes in ventilation design.

关键词： Migration time Underground mines Honey badger algorithm chaos mapping Back propagation neural network

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Synchronously scrambled diffuse image encryption method based on a new cosine chaotic map

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Chinese Physics B 2022年第8期31卷 296-309页

作者： Xiaopeng Yan Xingyuan Wang Yongjin Xian School of Information Science and Technology Dalian Maritime UniversityDalian 116026China Guangxi Key Laboratory of Multi-source Information Mining&Security Guangxi Normal UniversityGuilin 541004China

We present a new cosine chaotic mapping proved by chaos theory test and analysis such that the system has good cryptography properties, wide chaos range, simple structure, and good sensitivity to initial value, and the mapping can meet the needs of chaotic image encryption. Based on the cosine chaotic system, we propose a new encryption method. First,according to the cyclic characteristics of the mapping, the cyclic information wave is simulated. Second, the quasi-Doppler effect is used to synchronously scramble and diffuse the image to obfuscate the original pixel. Finally, the XOR diffusion of image pixels is carried out by information wave to further enhance the encryption effect. Simulation experiment and security analysis show that the algorithm has good security, can resist the common attack mode, and has good efficiency.

关键词： chaos mapping cosine mapping cyclic information wave doppler effect image encryption

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