This paper applies both the neural network and adaptive neuro-fuzzy inference system for forecasting short-term chaotic traffic volumes and compares the results. The architecture of the neural network consists of the ...This paper applies both the neural network and adaptive neuro-fuzzy inference system for forecasting short-term chaotic traffic volumes and compares the results. The architecture of the neural network consists of the input vector, one hidden layer and output layer. Bayesian regularization is employed to obtain the effective number of neurons in the hidden layer. The input variables and target of the adaptive neuro-fuzzy inference system are the same as those of the neural network. The data clustering technique is used to group data points so that the membership functions will be more tailored to the input data, which in turn greatly reduces the number of fuzzy rules. Numerical results indicate that these two models have almost the same accuracy, while the adaptive neuro-fuzzy inference system takes more time to train. It is also shown that although the effective number of neurons in the hidden layer is less than half the number of the input elements, the neural network can have satisfactory performance.展开更多
1,3-Butadiene plays a key role in modern synthetic chemistry and biochemistry because it is a key intermediate in the synthesis of many drugs.A new and effective method for the synthesis of 4-trifluoromethylated 1,3-b...1,3-Butadiene plays a key role in modern synthetic chemistry and biochemistry because it is a key intermediate in the synthesis of many drugs.A new and effective method for the synthesis of 4-trifluoromethylated 1,3-butadiene through the fluorinated Heck reaction catalyzed by Pd(0)is described.Without additives,1-chloro-3,3,3-trifluoropropene(an inexpensive CF3 structural unit that is harmless to ozone)reacts with enamide to synthesize 4-trifluoromethylated 1,3-butadienes with good yield,high regioselectivity and chemical selectivity,and strong tolerance of substrate functional groups such as alkynes,aldehyde,and ester groups.展开更多
文摘This paper applies both the neural network and adaptive neuro-fuzzy inference system for forecasting short-term chaotic traffic volumes and compares the results. The architecture of the neural network consists of the input vector, one hidden layer and output layer. Bayesian regularization is employed to obtain the effective number of neurons in the hidden layer. The input variables and target of the adaptive neuro-fuzzy inference system are the same as those of the neural network. The data clustering technique is used to group data points so that the membership functions will be more tailored to the input data, which in turn greatly reduces the number of fuzzy rules. Numerical results indicate that these two models have almost the same accuracy, while the adaptive neuro-fuzzy inference system takes more time to train. It is also shown that although the effective number of neurons in the hidden layer is less than half the number of the input elements, the neural network can have satisfactory performance.
基金the financial support by the National Natural Science Foundation of China(No.GZ1645)the Shaanxi Provincial Natural Science Basic Research Program(No.2021JLM-30)the Doctoral Scientific Research Foundation of Xi'an Polytechnic University(No.107020336).
文摘1,3-Butadiene plays a key role in modern synthetic chemistry and biochemistry because it is a key intermediate in the synthesis of many drugs.A new and effective method for the synthesis of 4-trifluoromethylated 1,3-butadiene through the fluorinated Heck reaction catalyzed by Pd(0)is described.Without additives,1-chloro-3,3,3-trifluoropropene(an inexpensive CF3 structural unit that is harmless to ozone)reacts with enamide to synthesize 4-trifluoromethylated 1,3-butadienes with good yield,high regioselectivity and chemical selectivity,and strong tolerance of substrate functional groups such as alkynes,aldehyde,and ester groups.
