Artificial Neural Networks Models for Flow Stress during High Temperature Plastic Deformation of Al-Li Alloy

Using gained experimental data to develop the models of stable flow stresses at high temperature plastic deformation by statistical methods for alloy materials, precision of the models is poor and at the same time the processes of modeling are complicated with great workload. On the basis of the data obtained on Gleeble-1500 Thermal Simulator,the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 Al-Li alloy have been developed with BP Artificial Neural Network method. The results show that the model on basis of BPNN is practical and it reflects the real feature of the deforming process. It states that the difference between the real value and the output of the model is in order of 5 percent.     

Building Enviornmental Monitoring System With COM

This article presents an implement of component using COM technology for collecting environmental monitoring data in environment monitoring system. The component makes the separation of data collection and data analysis available.Simultaneously by using the interface of connectable object in COM,itmakes the cooperation of the environment monitoring software with other parts of fault management software available,and also the seamless connection.It improves the system's performance by adding extensibility and potential cooperatibility.     

Selecting Bid with Reasonably Low Price Without Bottom Price Based On Sector Estimate

For raveling out the main shortage of tendering which is the reasonable sector is unreasonable of making the bid evaluation uncertain. In order to eliminate subjective factor, this paper quantificationally analyses the price in bidding and establishes the sector selecting bid model based on the sector estimate idea, which tries to provide a new method and academic basic for determining the reasonable sector. Finally, the article gives an example to prove that the model is feasible and effective and it tries to ensure the bidding assessment public, equitable and just.     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

Experimental Study on the Deformation Characteristics of Fine-Sandstone Under the Loading and Unloading Conditions

The deformation characteristics of the fine-sandstone is studied under the loading and unloading conditions at the three different deformation-rates and the two different stress-levels. The experimental results show that there is really the plastic-loop in the deformation curve for the loading deformation curve is different from the unloading deformation curve. But the plastic-loop is nearly unchangeable since the second circulate loading. The residual-deformation is be almost zero since the second circulate loading, and that the slope of the deformation curve increases as the deformation-rate increases, and that the residual-deformation increases as the stress-levels increases.     

Vibration & Noise Analysis on Double-ring Gear Reducer

Double-ring gear reducer with Central inputting shaft is studied. The basic structure of reducer as well as testing equipment, probe spot and testing method of Structure-borne noise and air-borne noise is presented. Based on frequency spectrum of each point, amplitude spectrum of structure-borne noise and testing results of air-borne noise, the authors analyze the vibration characters and latent faults of double-ring gear reducer, coming to the value and the cause of the noise, providing theoretical basis for proper design of the double-ring gear reducer and method of reducing its vibration and noise.     

New Algorithms for Data Discretization Based on Rough Set Theory

The discretization of real values is always one of the key problems to be solved in the domain of machine learning for its great contribution to speeding up the followed learning algorithms, cutting down the real demand of algorithms on running space and time, and improving the clustering capability of the ultimate learning results. The basic characteristics and framework of discretization approaches based on rough set model are analyzed at first, then the different measurements of the importance of candidate cuts are discussed and researched. Two new heuristic algorithms are put forward to finally select the useful cuts from a candidate set. The selected cuts of the two algorithms will adequately maintain the discernible relation of information systems for their full considering the specialty of rough set, which perfectly embodies the advantages of this theory. Moreover, excellent discretization results may be expected through these heuristic algorithms.