The Application of the Theory of 40 Hz EEG in the Stady of Chaotic States of EEG Signals

In this paper,the theory of 40 Hz EEG bursts is firstly used to judge whether thesubjects cooperate with us or not,and to determine the segments which can be processed for the studyof chaotic states of EEG signals.The theory,the realization of detecting method and the practiceapplication of 40 Hz EEG bursts are studied.     

A Study on Chaotic State of EEG Signal

In this paper.the chaotic theory is described briefly and the chaotic state ofEEG on thinking are studied. In this study. the method of detecting short bursts of 40 Hz EEG ac-tivity is firstly usedto dedermine the segments to be computed for analysis of the chaotic state ofEEG. therefore the reliability and stability of the analysis results are assured In this paper.thechaotic para meters of qa n titative analysis are studied and more then 30 subjects EEG are analysedfor the value of the fractional dimension and the maximal Lyapunov exponent.The results of exper-iments indicate that the value of the fractional dimension is valuable for clincal diagnosis and themaximal Lyapunov exponent is not sufficient for dignosis of disease.     

Analysis on 40 Hz ERP During Brain Transient Cognitive Performance

In this investigation 50 normal subjects were observed. Activities of EEG of 8 areas on both hemisphere during six different states were recorded. The author analyzed time ( T ), area( A ) and amplitude ( Amp ) of burst 40 Hz ERP recorded during different states and investigate the correlation's between 40 Hz ERP and age, sex,education background and scores of IQ. The time, area and amplitude of burst 40 Hz ERP are all significantly lower during rest states than those during orientation test, calculation test and visual spatial task test. During thinking process the increase of burst 40 Hz ERP is positive correlated with the scores in MMSE and WAIS. T is the most stable and sensitive marker. A affected by T and Amp, is stable but less sensitive than T. Amp is less sensitive than T and A.     

The Neural Network Method for Searching Graph Minimal Cut Set

The new neural network algorithm for searching graph minimal cut set,called NNMC algorithm, is established on the basis of construction of Hopfield Network energy function according to the concrete problem.In NNMC algorithm, which suffciently uses the fast convergence of Hopfield Network, a way to avoid the local minimum is carried out.     

A Kind of Fuzzy System Modelling and Control Based on Neural Networks

Combining artificial neural networks(ANN) with fuzzy system theory,a kind of modelling & control method of fuzzy system based on ANN is presented.The simulation researches have verified that the proposed approach can be applied effectively to a number of control systems which are defficult to build strict mathematical model.     

Study of Intelligent Fault Diagnostic System for a Kind of Power Plant

Based on the neural networks, object oriented technique, artificial intelligence technique and computer networks, an intelligent fault diagnosis system of the power plant whose need of the operation is presented. The architecture of software system , hardware system and corresponding databases is designed. The software of collecting data is established. The intelligent fault diagnosis system based on neural networks and object oriented technique is also developed. The physical system operation has been shown that the method mentioned above is feasible and effective in practice.     

Study on Nonlinear Dynamical Method for EEG Signal Processing

After studying the meaning of EEG signal processing using systems theory,the basic difficulties of the research on the EEG system and signal analysis are given,showing that it is hard to build model of the EEG system and signal.Hence,we introuduce the method of reconstructing the attractor in state spaces.Through the analysis of some experiments,the meaning of the presented method has been discussed.     

A Study on Artificial Neural Networks-based Medical Equipment Demand Forecast

In order to uncover the complex relation in the inventory data and lower the inventory level, based on the idea of black box method, all factors that influence demand are identified firstly. Then an initial forecast model of BP neural networks that adopt LM algorithm is established, and is trained using hospital inventory's history data. The interrelation's information of each factor that influences demand is stored in the link weights matrix W dispersedly. The final forecast model is obtained. We use the model to forecast the demand of medical equipment in Daping hospital. Based on it, the inventory cost is reduced enormously. The theory for the inventory system can be used to make management decision.     

A method for evolving the architecture and weights of neural networks via gene expression programming

An algorithm for automatic designation of the architecture and the weights of neural networks using gene expression programming (GEP) was presented. The fundamental ideas and procedures of the algorithm were discussed. The algorithm was improved to solve the problems of prematurity and lower variance rate. An application for neural networks designation was given. The experimental results indicate that the proposed GEP approach may evolve the architecture of neural network, and can obtain the weights more precisely. Compared to other conventional evolutional algorithms, GEP shows faster convergence.     

基于数值预报产品的地表温度预报方法研究

为了开展地表温度预报业务,提高逐日地表温度预报准确率,利用2007—2012年的ECMWF和T213数值预报产品资料及抚顺市的逐日地表温度资料,采用逐步回归分析方法和BP神经网络模型分别构建抚顺市地表温度预报模型,并对模型的精度进行检验。结果表明,地表温度与ECMWF的高度场、海平面气压场、温度场和T213的散度场、高度场、海平面气压场、地面气压场、海平面K指数、水汽通量、相对湿度、温度场、地面气温和场涡度场均呈显著相关。对预报模型进行精度检验显示,地表平均温度和地表最低温度的预报效果较好,≤3℃预报准确率均达到79%以上。2种模型对比显示,BP神经网络预报模型总体上优于逐步回归预报模型;逐步回归预报模型较BP神经网络预报模型稳定。     

Applications of the Fuzzy Neural Networks to Short term Load Forecasting

This paper presents a fuzzy neural network approach to short term load forecasting.It can predict the hourly loads for next day or next week with the fuzzy information.The practical examples have proved the efficiencies of the proposed approach.     

热浸法提取花生壳中多酚类物质的工艺研究

研究了热浸法提取花生壳中多酚类物质的工艺,对影响多酚得率的因素进行了单因素试验,通过正交试验确定最佳工艺条件为:乙醇体积分数为65%,浸提温度为75℃,料液比为1∶30,浸提时间为5h,此条件下多酚类物质的提取率为5.66mg/g。     

Dynamic Control Model for the Secondary Cooling of Slab Casting Based on Neural Networks

A dynamic control model for the secondary cooling of slab casting is presented to reduce the difference between the actual temperature and the goal surface temperature of slab. The model, which is based on the BP neural networks for forecasting the temperature and the fuzzy neural networks for dynamically controlling the water in the secondary cooling in the continuous casting, could timely adjust and allocate the water according to the speed and temperature of slab. A series of tests have been conducted based on inputs of the No. 2 slab caster in a steel plant. It has been shown that the model, which integrate the charateristics of water controlling problem in secondary cooling into the temperature status of slab during the cooling process, can control the water in secondary cooling efficiently and dynamically according to the situation of actual production.     

皂化对枸杞色素提取效果的影响

采用单因素试验和正交试验,以提取物中色素含量为考察指标,对枸杞色素提取过程中的皂化处理进行了研究。结果表明,各因素的影响程度依次为:皂化温度>NaOH质量分数>皂化液与枸杞干果果肉的比例(液料比)>皂化时间。确定了枸杞皂化处理的最佳条件为:皂化温度40℃,NaOH质量分数1.0%,液料比4:1,皂化时间40min。     

皂化法提取胞内辅酶Q_(10)的研究

以根癌土壤杆菌为出发菌株,采用发酵法生产辅酶Q10,考察了破壁方法、皂化温度、皂化时间、加碱量、皂化顺序对辅酶Q10提取率的影响,试验得到皂化的最佳条件为:皂化温度60℃,皂化时间30min,皂化液与破碎液比例为5∶2。与未皂化相比,皂化后的细胞碎片经固液萃取后得到的辅酶Q10提取量提高了39.65%,并且消除了杂质对辅酶Q10测定的影响,该方法可行性强,具有广阔的发展前景。     

烤烟烟叶腺毛分泌物提取方法初探

为探索烤烟烟叶腺毛分泌物提取效果最佳的方法,以烤烟品种K326、云烟85和红花大金元为材料,采用二氯甲烷作为溶剂,比较不同提取级数和不同提取时间前后叶片重量的变化。结果表明,在烟叶腺毛分泌物提取方法的不同提取级数的效果比较中,3个烤烟品种均以前3级提取的变化最明显,而之后增加提取级数,叶片重量变化不明显;不同提取时间对叶片的重量变化影响不大。这说明采用3级提取作为烤烟叶片腺毛分泌物的提取方法比较适宜     

超声波法从小浆果树莓中提取果胶的研究

以小浆果树莓果实为原料,采用咔唑比色的方法,利用超声波法研究了超声波提取时间、超声功率和料液比对果胶提取量的影响,在此基础上进行L9(33)正交试验,确定了超声波法提取树莓果实中果胶的最佳提取条件为:料液比为1∶80,超声功率为400 W,超声波提取时间35 min,果胶含量可达1.21%。     

果胶酶法提取黑穗醋栗果实中多糖工艺的研究

研究了果胶酶法提取黑穗醋栗果实中活性多糖的最佳提取工艺,进行了单因素实验,考察温度、pH值、料液比及酶添加量对黑穗醋栗多糖提取率的影响;在此基础上,采用L9(43)正交试验,确定了最佳提取工艺条件:温度为60℃,pH值为4.5,料液比为1∶10,酶添加量为2.0%。在最佳工艺条件下,多糖的提取率为8.23%。