关于择优逻辑单调性的几个结果

本文在Ｓｈｏｈａｍ给出的择优模和择优蕴涵概念的基础上．进一步研究了择优逻辑的单调性．首先，讨论了择优逻辑的若干基本性质，并给出了单调性的一个充要条件；其次，证明了单调性与反证律等价，并给出了单调性的一个更为简洁的充要条件；最后，讨论了解释集合是归纳集时的单调性，证明了单调性与择优蕴涵的退化等价．这些结果，揭示了择优蕴涵、传统蕴涵、单调性、反证律之间的关系．

Phase-field simulation of forced flow effect on random preferred growth direction of multiple grains

The random distribution problem of dendrite preferred growth direction was settled by random grid method.This method was used to study the influence of forced laminar flow effect on multiple grains during solidification.Taking high pure succinonitrile （SCN） undercooled melt as an example,the forced laminar flow effect on multiple grains was studied by phase-field model of single grain which coupled with flow equations at non-isothermal condition.The simulation results show that the random grid method can reasonably settle the problem of random distribution and is more effective.When the solid fraction is relatively low,melt particles flow around the downstream side of dendrite,and the flow velocity between two dendrite arms becomes high.At the stage of solidification time less than 1800Δt,every dendrite grows freely;the upstream dendrites are stronger than the downstream ones.The higher the melt flow rate,the higher the solid fraction.However,when the solid fraction is relatively high,the dendrite arm intertwins and only a little residual melt which is not encapsulated can flow;the solid fraction will gradually tend to equal to solid fraction of melt without flow.

Small World Effects in a Harmonious Unifying Hybrid Preferential Model Networks

Small worm effects in the harmonious unifying hybrid preferential model （HUHPM） networks are studied both numerically and analytically. The idea and method of the HUHPM is applied to three typical examples of unweighted BA model, weighted BBV model, and the TDE rnodel, so-called HUHPM-BA, HUHPM-BBV and HUHPM- TDE networks. Comparing the HUHPM with current typical models above, it is found that the HUHPM networks has the smallest average path length and the biggest average clustering coefficient. The results demonstrate that the HUHPM is more suitable not only for the un-iveighted models but also for the weighted models.

Application of fuzzy optimal selection of similar slopes to the evaluation of slope stability

The numerical calculation method is widely used in the evaluation of slope stability,but it cannot take the randomness and fuzziness into account that exist in rock and soil engineering objectively.The fuzzy optimization theory is thus introduced to the evaluation of slope stability by this paper and a method of fuzzy optimal selection of similar slopes is put forward to analyze slope stability.By comparing the relative membership degrees that the evaluated object sample of slope is similar to the source samples of which the stabilities are detected clearly,the source sample with the maximal relative membership degree will be chosen as the best similar one to the object sample,and the stability of the object sample can be evaluated by that of the best similar source sample.In the process many uncertain influential factors are considered and characteristics and knowledge of the source samples are obtained.The practical calculation indicates that it can achieve good results to evaluate slope stability by using this method.

Research on group expandable optimization decision-making model for construction programme choice

Aiming at the decision-making problem of construction programme choice,this paper advanced a new group expandable optimization decision-making model.Various factors were comprehensively considered,and the new multi-attribute evaluation index system was established.Based on the assumption that decision-makers were rational,this paper formed a group of rational preferences through extracting the personal preferences pertinently,so the decision-makers position matrix was determined.The decision-makers position matrix integrated values given by group decision-makers to construction programme comprised a matrix,of which the entropy theory for datamining was adopted in this paper to determine the attribute weights.A decision was made by using the extension decision method.Eventually,the feasibility and practicability of the model were verified by the example.

The green fuel from carbon waste： optimization and product selectivity model studies

Increase in greenhouse gases, has made scientists to substitute alternative fuels for fossil fuels. Nowadays, converting biomass into liquid by Fischer-Tropsch synthesis is a major concern for alternative fuels （gasoline, diesel etc.）. Selectivity of Fischer-Tropsch hydrocarbon product （green fuel） is an important issue. In this study, the experimental data has been obtained from three factors; temperature, H2/CO ratio and pressure in the fixed bed micro reactor. T = 543-618 （K）, P = 3-10 （bar）, H2/CO = 1-2 and space velocity = 4500 （l/h） were the reactor conditions. The results of product modeling for methane （CH4）, ethane （C2H6）, ethylene （C2H4） and CO conversion with experimental data were compared. The effective parameters and the interaction between them were investigated in the model. H2/CO ratio and pressure and interaction between pressure and H2/CO in ethane selectivity model and CO conversion and interaction between temperature and H2/CO ratio in methane selectivity model and ethylene gave the best results. To determine the optimal conditions for light hydrocarbons, ANOVA and RSM were employed. Finally, products optimization was done and results were concluded.

Customization Using Fuzzy Recommender Systems

We discuss some methods for constructing recommender systems. An important feature of the methods studied here is that we assume the availability of a description, representation, of the objects being considered for recommendation. The approaches studied here differ from collaborative filtering in that we only use preferences information from the individual for whom we are providing the recommendation and make no use the preferences of other collaborators. We provide a detailed discussion of the construction of the representation schema used. We consider two sources of information about the users preferences. The first are direct statements about the type of objects the user likes. The second source of information comes from ratings of objects which the user has experienced.

Optimizing selection of bridge raft based on fuzzy matter-element model and combination weighting

It＇ s a necessary selection to support the maneuver across Yangtze River by floating bridge constructed by portable steel bridge and civilian ships. It is a comprehensive index for the scheme of bridge raft, containing a variety of technical factors and uncertainties. The optimization is the selection in the constructing time, quantity of equipments and man power. Based on the calculation result of bridge rafts, an evaluating system is established, consisting of index of spacing between interior bays, raft length, truss numbers, operation difficulty and maximal bending stress. A fuzzy matter element model of optimizing selection of bridge rafts was built up by combining quantitative analysis with qualitative analysis. The method of combination weighting was used to calculate the value of weights index to reduce the subjective randomness. The sequence of schemes and the optimization resuh were gained finally based on euclid approach degree. The application result shows that it is simple and practical.

Frame complexity optimized selection for H.264/AVC video coding

To improve the coding performance of H.264/AVC, this paper proposes a rate control scheme composed of a novel flame complexity optimized selection and a quantization parameter （QP） value computation approach. First, it extracts the frame coding complexity from two rate distortion models, and then introduces five statistic modes to estimate the frame coding complexity. An optimal mode is selected according to the coding efficiency. Finally the paper presents a novel QP calculation method for the H.264/AVC rate control. Experimental results show that the proposed algorithra outperforms the algorithm integrated in the 3M model in obtaining precise frame coding complexity, achieving robust buffer control and improving coding quality. And the improving visual quality is high up to 0.90dB for CIF sequences.

Parameter selection in time series prediction based on nu-support vector regression

The theory of nu-support vector regression (Nu-SVR) is employed in modeling time series variationfor prediction. In order to avoid prediction performance degradation caused by improper parameters, themethod of parallel multidimensional step search (PMSS) is proposed for users to select best parameters intraining support vector machine to get a prediction model. A series of tests are performed to evaluate themodeling mechanism and prediction results indicate that Nu-SVR models can reflect the variation tendencyof time series with low prediction error on both familiar and unfamiliar data. Statistical analysis is alsoemployed to verify the optimization performance of PMSS algorithm and comparative results indicate thattraining error can take the minimum over the interval around planar data point corresponding to selectedparameters. Moreover, the introduction of parallelization can remarkably speed up the optimizing procedure.

Choice of weights in FMA estimators under general parametric models

The choice of weights in frequentist model average estimators is an important but difficult problem. Liang et al. (2011) suggested a criterion for the choice of weight under a general parametric framework which is termed as the generalized OPT (GOPT) criterion in the present paper. However, no properties and applications of the criterion have been studied. This paper is devoted to the further investigation of the GOPT criterion. We show that how to use this criterion for comparison of some existing weights such as the smoothed AIC-based and BIC-based weights and for the choice between model averaging and model selection. Its connection to the Mallows and ordinary OPT criteria is built. The asymptotic optimality on the criterion in the case of non-random weights is also obtained. Finite sample performance of the GOPT criterion is assessed by simulations. Application to the analysis of two real data sets is presented as well.

A Forward Selection Method on Customer Credit

In this paper, we discuss a selection and evaluation method of customer credit for the commercial bank loans operation, and put forth a forward selection model by optimization techniques. At last, we also give an example to analyze its application.