The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived o...The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model.These chaotic sequences,generated using 2D-SIMM model,are sensitive to initial conditions.In the proposed algorithm,these initial conditions are optimized using JAYA optimization algorithm.Correlation coefficient and entropy are considered asfitness functions in this study to evaluate the best solution for initial conditions.The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms.In addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator.With optimization,the correlation coefficient was-0.014096 and without optimization,it was 0.002585.展开更多
针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进IN...针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。展开更多
To ensure the safe transmission of image information in communication, and improve the security performance of image encryption algorithm, we proposed a color image encryption algorithm with higher security based on c...To ensure the safe transmission of image information in communication, and improve the security performance of image encryption algorithm, we proposed a color image encryption algorithm with higher security based on chaotic system. Firstly, the 2-dimensional Cubic ICMIC modulation map(2D-CIMM) is designed, which has simple form, easy to construct, and high Spectral Entropy(SE) complexity. Secondly, the hash values of the original image are used to update the initial values of the 2D-CIMM map in real time, which increases the sensitivity of the image encryption algorithm to the plaintext and improves the finite precision effect. Finally, the permutation and diffusion processes of the encryption algorithm based on bit-level are performed. In addition, simulation and performance analysis show that the proposed algorithm has higher security.展开更多
文摘The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model.These chaotic sequences,generated using 2D-SIMM model,are sensitive to initial conditions.In the proposed algorithm,these initial conditions are optimized using JAYA optimization algorithm.Correlation coefficient and entropy are considered asfitness functions in this study to evaluate the best solution for initial conditions.The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms.In addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator.With optimization,the correlation coefficient was-0.014096 and without optimization,it was 0.002585.
文摘针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。
基金the National Natural Science Foundation of China (Grant Nos. 61161006 and 61573383)
文摘To ensure the safe transmission of image information in communication, and improve the security performance of image encryption algorithm, we proposed a color image encryption algorithm with higher security based on chaotic system. Firstly, the 2-dimensional Cubic ICMIC modulation map(2D-CIMM) is designed, which has simple form, easy to construct, and high Spectral Entropy(SE) complexity. Secondly, the hash values of the original image are used to update the initial values of the 2D-CIMM map in real time, which increases the sensitivity of the image encryption algorithm to the plaintext and improves the finite precision effect. Finally, the permutation and diffusion processes of the encryption algorithm based on bit-level are performed. In addition, simulation and performance analysis show that the proposed algorithm has higher security.
