Monetary policy rules：Forward-looking and backward-looking in an overlapping generations model

In the framework of an overlapping generations model, forward-looking monetary policy roles and backward-looking monetary policy rules were investigated. It is shown that the monetary steady state is more likely to be indeterminate under an active forwardlooking rule than under the corresponding backward-looking rule. It is also shown that backward-looking roles can render the monetary steady state unstable.

Mining multilevel spatial association rules with cloud models

The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules. Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.

Incorporating Linguistic Rules in Statistical Chinese Language Model for Pinyin-to-character Conversion

An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.

Research on Urban Building Parametric Modelling Method Based on CityEngine

With the advancement of technology and the development of cities,urban planning and management methods are also constantly improving.From paper-based assignments to modern digitization,new technologies have enabled more efficient design and management for cities.3D modeling can used to simulate the urban environment,which can assist in urban planning and management.However,large-scale modeling cannot be achieved through existing modeling methods,and there are still some shortcomings in the maintenance of the model.Therefore,this article proposes a Computer Generated Architecture(CGA)parametric 3D modeling method based on CityEngine.Research on expanding and customizing modeling rules to create indoor and outdoor modeling rule templates for buildings and methods for generating urban 3D models have been carried out.The results have shown that the completed model can be displayed on different platforms thanks to parameterized modeling.The model can be modified easily and directly applied to the analysis and decision-making of urban planning schemes.

Spatiotemporal evolution rule of rocks fracture surrounding gob-side roadway with model experiments

A series of plane-strain physical model experiments are carried out to study the spatiotemporal evolution rule of rocks fracture surrounding gob-side roadway, which is subjected to the pressure induced by the mining process. The digital photogrammetry technology and large deformation analysis method are applied to measure the deformation and fracture of surrounding rocks. The experimental results indicate that the deformation and fracture of coal pillars are the cause to the instability and failure of the surrounding rocks. The spatiotemporal evolution rule of the rock deformation and fracture surrounding gob-side roadway is obtained. The coal pillar and the roof near coal pillar should be strengthened in support design. The engineering application results also can provide a useful guide that the combined support with wire meshes, beam, anchor bolt and cable is an effective method.

Transforming Model Oriented Program into Android Source Code Based on Drools Rule Engine

Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper presents the model transformation approach for textual model oriented programs Umple (UML Programming Language) to generate android applications (apps). The proposed approach improved the generation of android source code by using Drools transformation rules and introducing new concern in model driven mobile engineering. The major objective of proposed transformation approach intends to address consistency between source and target model and also intends to handle productivity issues in model driven software development. The main results of model transformation approach are Java class for model layer, XML file for view layer and android activity class for controller layer. Results show that proposed approach achieves high consistency between source and target model and also improves model transformation productivity.

The Books Recommend Service System Based on Improved Algorithm for Mining Association Rules

The Apriori algorithm is a classical method of association rules mining.Based on analysis of this theory,the paper provides an improved Apriori algorithm.The paper puts foward with algorithm combines HASH table technique and reduction of candidate item sets to enhance the usage efficiency of resources as well as the individualized service of the data library.

COD_(Cr) leaching rules of municipal solid waste in Songtao Reservoir,Hainan Province,China

By the means of static leaching experiment and dynamic leaching experiment,CODCr leaching rules of dumped MSW(Municipal Solid Waste) in Songtao Reservoir,Hainan Province,China,were studied. And according to academic experience and fitted results of experiment data,the models of CODCr leaching rules in the leaching condition were deduced. The static leaching experiment indicates that,both in water-changing section and no-water-changing section,the ratio of liquid to solid has a remarkable influence on CODCr leaching concentration. The exponential model could be established to approximately describe CODCr leaching rules and the curve fits well. The dynamic leaching experiment indicates that,leaching rules of MSW can be approximately described by power model,which can well fit the leaching experiment data. By the contrast of the static leaching experiment and dynamic leaching experiment,the differences of CODCr leaching rules between the two experiments are significant. By the exponential model,the average static leaching rate of CODCr is calculated as 882.24 mg/(kg·d) for water-changing section and 320.39 mg/(kg·d) for no-water-changing section; by the power model,the average dynamic leaching rate of CODCr is 208.77 mg/(kg·d).

New insight into prediction of phase behavior of natural gas hydrate by different cubic equations of state coupled with various mixing rules

Progress in hydrate thermodynamic study necessitates robust and fast models to be incorporated in reservoir simulation softwares. However, numerous models presented in the literature makes selection of the best,proper predictive model a cumbersome task. It is of industrial interest to make use of cubic equations of state(EOS) for modeling hydrate equilibria. In this regard, this study focuses on evaluation of three common EOSs including Peng–Robinson, Soave–Redlich–Kwong and Valderrama–Patel–Teja coupled with van der Waals and Platteeuw theory to predict hydrate P–T equilibrium of a real natural gas sample. Each EOS was accompanied with three mixing rules, including van der Waals(vd W),Avlonitis non-density dependent(ANDD) and general nonquadratic(GNQ). The prediction of cubic EOSs was in sufficient agreement with experimental data and with overall AARD% of less than unity. In addition, PR plus ANDD proved to be the most accurate model in this study for prediction of hydrate equilibria with AARD% of 0.166.It was observed that the accuracy of cubic EOSs studied in this paper depends on mixing rule coupled with them,especially at high-pressure conditions. Lastly, the present study does not include any adjustable parameter to be correlated with hydrate phase equilibrium data.

Forward heuristic breadth-first reasoning based on rule match for biomass hybrid soft-sensor modeling in fermentation process

Biomass is a key parameter in fermentation process, directly influencing the performance of the fermentation system as well as the quality and yield of the targeted product. Hybrid soft-sensor modeling is a good method for on-line estimation of biomass. Structure of hybrid soft-sensor model is a key to improve the estimating accuracy. In this paper, a forward heuristic breadth-first reasoning approach based on rule match is proposed for constructing structure of hybrid model. First, strategy of forward heuristic reasoning about facts is introduced, which can reason complex hybrid model structure in the event of few known facts. Second, rule match degree is defined to obtain higher esti- mating accuracy. The experiment results of Nosiheptide fermentation process show that the hybrid modeling process can estimate biomass with higher accuracy by adding transcendental knowledge and partial mechanism to the process.

Hiding Sensitive XML Association Rules With Supervised Learning Technique

In the privacy preservation of association rules, sensitivity analysis should be reported after the quantification of items in terms of their occurrence. The traditional methodologies, used for preserving confidentiality of association rules, are based on the assumptions while safeguarding susceptible information rather than recognition of insightful items. Therefore, it is time to go one step ahead in order to remove such assumptions in the protection of responsive information especially in XML association rule mining. Thus, we focus on this central and highly researched area in terms of generating XML association rule mining without arguing on the disclosure risks involvement in such mining process. Hence, we described the identification of susceptible items in order to hide the confidential information through a supervised learning technique. These susceptible items show the high dependency on other items that are measured in terms of statistical significance with Bayesian Network. Thus, we proposed two methodologies based on items probabilistic occurrence and mode of items. Additionally, all this information is modeled and named PPDM (Privacy Preservation in Data Mining) model for XARs. Furthermore, the PPDM model is helpful for sharing markets information among competitors with a lower chance of generating monopoly. Finally, PPDM model introduces great accuracy in computing sensitivity of items and opens new dimensions to the academia for the standardization of such NP-hard problems.

Active suspension control of a one-wheel car model using single input rule modules fuzzy reasoning and a disturbance observer

This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the pre- condition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model.

Comparative Study of the Performance of M5-Rules Algorithm with Different Algorithms

The effort invested in a software project is probably one of the most important and most analyzed variables in recent years in the process of project management. The determination of the value of this variable when initiating software projects allows us to plan adequately any forthcoming activities. As far as estimation and prediction is concerned there is still a number of unsolved problems and errors. To obtain good results it is essential to take into consideration any previous projects. Estimating the effort with a high grade of reliability is a problem which has not yet been solved and even the project manager has to deal with it since the beginning. In this study, performance of M5-Rules Algorithm, single conjunctive rule learner and decision table majority classifier are experimented for modeling of Effort Estimation of Software Projects and performance of developed models is compared with the existing algorithms namely Halstead, Walston-Felix, Bailey-Basili, Doty in terms of MAE and RMSE. The proposed techniques are run in the WEKA environment for building the model structure for software effort and the formulae of existing models are calculated in the MATLAB environment. The performance evaluation criteria are based on MAE and RMSE. The result shows that the M5-Rules have the best performance and can be used for the effort estimation of all types of software projects.

Generation Rules in POMA Architecture

Another component in Pattern-Oriented and Model-Driven Architecture (POMA) is the concept of model generation. The generation code of models is the process of creating a source code from a model using generation rules. In this paper, we present the generation rules that are used to support the automated code generator of POMA architecture to generate the source code of the entire interactive system. These Platform-Specific Model (PSM) models are based on patterns which illustrate how several individual models of patterns can be generated at different levels of abstraction such as PSM models to source code in the development of interactive systems.

A Lecture of the Taylor Rule from the Sandpile Model

Sandpile phenomena in dynamic systems in the vicinity of criticality always appeal to a sudden break of stability with avalanches of different sizes due to minor perturbations. We can view the intervention of the Central Banks on the rate of interest as a perturbation of the economic system. It is an induced perturbation to a system that fare in vicinity of criticality according to the conditions of stability embedded in the equations of the neoclassical model. An alternative reading of the Taylor Rule is proposed in combination with the Sandpile paradigm to give an account of the economic crisis as an event like an avalanche, that can be triggered by a perturbation, as is the intervention of the Central Bank on the interest rate.

Fast generation method of fuzzy rules and its application to flux optimization in process of matter converting

A fast generation method of fuzzy rules for flux optimization decision-making was proposed in order to extract the linguistic knowledge from numerical data in the process of matter converting. The fuzzy if-then rules with consequent real number were extracted from numerical data, and a linguistic representation method for deriving linguistic rules from fuzzy if-then rules with consequent real numbers was developed. The linguistic representation consisted of two linguistic variables with the degree of certainty and the storage structure of rule base was described. The simulation results show that the method involves neither the time-consuming iterative learning procedure nor the complicated rule generation mechanisms, and can approximate complex system. The method was applied to determine the flux amount of copper converting furnace in the process of matter converting. The real result shows that the mass fraction of Cu in slag is reduced by 0.5%.

Intrusion Detection Using Ensemble Wrapper Filter Based Feature Selection with Stacking Model

The number of attacks is growing tremendously in tandem with the growth of internet technologies.As a result,protecting the private data from prying eyes has become a critical and tough undertaking.Many intrusion detection solutions have been offered by researchers in order to decrease the effect of these attacks.For attack detection,the prior system has created an SMSRPF(Stacking Model Significant Rule Power Factor)classifier.To provide creative instance detection,the SMSRPF combines the detection of trained classifiers such as DT(Decision Tree)and RF(Random Forest).Nevertheless,it does not generate any accuratefindings that are adequate.The suggested system has built an EWF(Ensemble Wrapper Filter)feature selection with SMSRPF classifier for attack detection so as to overcome this problem.The UNSW-NB15 dataset is used as an input in this proposed research project.Specifically,min–max normalization approach is used to pre-process the incoming data.The feature selection is then carried out using EWF.Based on the selected features,SMSRPF classifiers are utilized to detect the attacks.The SMSRPF is integrated with the trained classi-fiers such as DT and RF to create creative instance detection.After that,the testing data is classified using MCAR(Multi-Class Classification based on Association Rules).The SRPF judges the rules correctly even when the confidence and the lift measures fail.Regarding accuracy,precision,recall,f-measure,computation time,and error,the experimental findings suggest that the new system outperforms the prior systems.

Stability and stabilization of discrete T-S fuzzy time-delay system based on maximal overlapped-rules group

The problems of stability and stabilization for the discrete Takagi-Sugeno（T-S） fuzzy time-delay system are investigated.By constructing a discrete piecewise Lyapunov-Krasovskii function（PLKF） in each maximal overlapped-rules group（MORG）,a new sufficient stability condition for the open-loop discrete T-S fuzzy time-delay system is proposed and proved.Then the systematic design of the fuzzy controller is investigated via the parallel distributed compensation control scheme,and a new stabilization condition for the closed-loop discrete T-S fuzzy time-delay system is proposed.The above two sufficient conditions only require finding common matrices in each MORG.Compared with the common Lyapunov-Krasovskii function（CLKF） approach and the fuzzy Lyapunov-Krasovskii function（FLKF） approach,these proposed sufficient conditions can not only overcome the defect of finding common matrices in the whole feasible region but also largely reduce the number of linear matrix inequalities to be solved.Finally,simulation examples show that the proposed PLKF approach is effective.

泥岩卸荷损伤-水次序作用下的劣化规律研究

工程开挖建设导致软岩形成卸荷损伤,其在水-岩作用下的劣化特征与卸荷损伤程度密切相关。以巴东地区红层泥岩为研究对象,设计进行了泥岩卸荷损伤模拟试验,随后对卸荷损伤泥岩试样进行水-岩作用试验,结果显示:卸荷损伤导致泥岩局部矿物颗粒形态破坏、微裂缝发育,在后续水-岩作用下颗粒间胶结程度持续弱化,孔隙、裂缝进一步扩展。宏细观参数随水-岩作用时间的增长,其中质量m呈现先上升后骤然下降再趋于稳定的趋势,纵波波速P呈现先减少后上升的趋势,体积应变εv呈现逐渐增大的趋势,分形维数K呈逐渐增长的趋势;且各参数的增长速率均随卸荷损伤程度D的增大呈幂函数增加,当D≥0.49时,各参数的增长速率急剧增大;确定以质量、纵波波速、体积应变和分形维数作为与水反应系统的变量,并运用非线性动力学理论建立了水-岩作用下的泥岩劣化模型,并验证了模型的合理性。研究结果表明所建模型能表征卸荷损伤泥岩在水-岩作用下的宏细观特征参数变化趋势提供一定理论参考。