Formal languages, part theory, and change

A general definition of interpreted formal language is presented. The notion “is a part of" is formally developed and models of the resulting part theory are used as universes of discourse of the formal languages. It is shown that certain Boolean algebras are models of part theory.

With this development, the structure imposed upon the universe of discourse by a formal language is characterized by a group of automorphisms of the model of part theory. If the model of part theory is thought of as a static world, the automorphisms become the changes which take place in the world. Using this formalism, we discuss a notion of abstraction and the concept of definability. A Galois connection between the groups characterizing formal languages and a language-like closure over the groups is determined.

It is shown that a set theory can be developed within models of part theory such that certain strong formal languages can be said to determine their own set theory. This development is such that for a given formal language whose universe of discourse is a model of part theory, a set theory can be imbedded as a submodel of part theory so that the formal language has parts which are sets as its discursive entities.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

Application of rough set-based analysis to extract spatial relationship indicator rules: An example of land use in Pearl River Delta

Spatial relations, reflecting the complex association between geographical phenomena and environments, are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization, an important geographical issue, is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter, the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong, located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan, Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan, Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.

吐合盆地鲁克沁构造带断块油藏形成机制及油藏预测

Lukeqin arc belt is a compound structure generated by multi-movements and composed of 6 sub-structural zones, which are connected by Huoyanshan Mountain. General characteristics of the arc belt are multi-patterns of structure, multi-phases for petroleum, multi-types of trap and multi-layers for reservoirs. As a part of the eastern Lukeqin arc belt located on the south of Taibei depression, Lukeqin structural zone behaves as a complex faulted-fold zone, in which the formation and distribution of hydrocarbons are controlled by structures. As the dominant source of dynamics for the second migration of hydrocarbon, structure stress field is closely related with the potentials of hydrodynamics. Results derived from the simulations of stress field by finite element method indicate that the northwest tending faults prefer seal to the northeast tending ones. The reason is that the northwest tending faults were squeezed more strongly than the northeast tending ones. Therefor, the northeast tending faults become always the paths for oil to migrate southeastward. Lukeqin structural zone is the main site for oil to concentration because it is surrounded by high stress. Situated on the front of the foreland basin of Turpan-Hami, Lukeqing arc belt is a dam to hold back the southward migrating oil from Shengbei depression. The axis line of Shenquan-Shengnan-Yanmuxi, Lukeqin and Yubei controls the migrating paths and concentrating process of oil and gas. Results derived from stress simulation and structure analyses indicate consistently that both Yubei and Lukeqin structural zones are the favorite areas for oil to migrate. The generally southward paths for oil to migrate out of Taibei depression can be two ways. One of them is from Taibei depression to Yubei structural zone and the other is from Taibei depression to Lukeqin structural zone. By the both ways, oil migrated upward along the faults and southeastward along the structural axis to concentrate in either Permian or Triassic system. The newly ascertained path for oil migration, which is accurately southeastward instead of coarsely southward, indicates the directions for further explorations on the compound Lukeqin block zone. Five kinds of seal models of fault are all found in Lukeqin block zone by studying the seal features of faults occurred in the zone. Having studied the fault seal and their controlling factors by fuzzy set method, the paper deems that the northwest tended faults are better than the northeast tended ones for oil to concentrate. The most important factors to decide the seal extent of faults in this zone are the characteristics of main stress and fluids instead of capillary pressure differences between the two sides of fault and smear mud factors. There exist seal differences not only between the faults of different time but also between the sections within a fault due to the variation of depths, strata and positions. The general distribution rules of reservoirs were dominated by the seal characteristics of a fault during the time reservoirs formed. While the current features of fault seal decide the conservation of reservoirs and heights of oil accumulations. Seal or not of a fault is not absolute because the essential for fault to seal is the distribution of permeability of fault zone. Therefor, the multi cyclical activities of faults create the space-time variation of seal features of the fault. Totally, the seal extent of the faults within the area is not as perfect as to accumulate ordinary crude. Crude oil can only be sealed when it becomes viscous. Process for crude oil to become viscous and viscous happened strongly because of the fault-fold movements. Shallowly burying and even revealing of the objective layers of the reservoirs made the crude oil to be thickened by water washing biologically degradation and oxidation degradation. The northwestward deepening during or after the reservoir formation of the structural zone provided the power for oil to migrate one or more times. The main reason for oil accumulation is the formation of Lukeqin block zone during Xishanyao stage, middle Jurassic Period, Early Yanshanian Movement. While the main reason for reservoir conservation is the placidity of Triassic blocks after the formation of reservoirs. Contrasting to former opinions, it is concluded that the reservoirs in Lukeqin zone, including viscous reservoirs, were formed by one time but not more times. So the author proposes the opinion that the reservoirs of viscous oil were formed by viscous oil migration under the conditions of aptitude sets of fault seals controlled by fluid and other factors. To grope the distribution rules outside Taibei depression and discuss the formation mechanism of Anjurassic reservoirs, it is necessary to study the dominate factors for the formation of reservoirs in Lukeqin structural zone such as structural stress, fault seals and thickening mechanism of crude oil. Also, the necessary studies are the key to break through the Taibei depression and Anjurassic systems. Therefor, they are significant for the future exploration and reserve increasing of hydrocarbon within the Turpan-Hami basin. The paper studied the distribution rules of block reservoirs and forecasted the favorable zones for further exploration in Turpan-Hami basin. Conclusions can be useful for not only the exploration in the area but also the theory consult in the adjacent areas.

Rough feature selection for intelligent classifiers

Q. Shen. Rough feature selection for intelligent classifiers. LNCS Transactions on Rough Sets, 7:244-255, 2007.

Rough sets, their extensions and applications

Q. Shen and R. Jensen, 'Rough sets, their extensions and applications,' International Journal of Automation and Computing (IJAC), vol. 4, no. 3, pp. 217-218, 2007.

A computational intelligent approach to multi-factor analysis of violent crime information systems

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

L-Fuzzy Structured Query Language

Lattice valued fuzziness is more general than crispness or fuzziness based on the unit interval. In this work, we present a query language for a lattice based fuzzy database. We define a Lattice Fuzzy Structured Query Language (LFSQL) taking its membership values from an arbitrary lattice L. LFSQL can handle, manage and represent crisp values, linear ordered membership degrees and also allows membership degrees from lattices with non-comparable values. This gives richer membership degrees, and hence makes LFSQL more flexible than FSQL or SQL. In order to handle vagueness or imprecise information, every entry into an L-fuzzy database is an L-fuzzy set instead of crisp values. All of this makes LFSQL an ideal query language to handle imprecise data where some factors are non-comparable. After defining the syntax of the language formally, we provide its semantics using L-fuzzy sets and relations. The semantics can be used in future work to investigate concepts such as functional dependencies. Last but not least, we present a parser for LFSQL implemented in Haskell.

GA approach for finding Rough Set decision rules based on bireducts

Feature selection plays an important role in knowledge discovery and data mining nowadays. In traditional rough set theory, feature selection using reduct - the minimal discerning set of attributes - is an important area. Nevertheless, the original definition of a reduct is restrictive, so in one of the previous research it was proposed to take into account not only the horizontal reduction of information by feature selection, but also a vertical reduction considering suitable subsets of the original set of objects. Following the work mentioned above, a new approach to generate bireducts using a multi--objective genetic algorithm was proposed. Although the genetic algorithms were used to calculate reduct in some previous works, we did not find any work where genetic algorithms were adopted to calculate bireducts. Compared to the works done before in this area, the proposed method has less randomness in generating bireducts. The genetic algorithm system estimated a quality of each bireduct by values of two objective functions as evolution progresses, so consequently a set of bireducts with optimized values of these objectives was obtained. Different fitness evaluation methods and genetic operators, such as crossover and mutation, were applied and the prediction accuracies were compared. Five datasets were used to test the proposed method and two datasets were used to perform a comparison study. Statistical analysis using the one-way ANOVA test was performed to determine the significant difference between the results. The experiment showed that the proposed method was able to reduce the number of bireducts necessary in order to receive a good prediction accuracy. Also, the influence of different genetic operators and fitness evaluation strategies on the prediction accuracy was analyzed. It was shown that the prediction accuracies of the proposed method are comparable with the best results in machine learning literature, and some of them outperformed it.

Some Problems In Algebra And Topology A Study Of Fuzzy Convexity With Special Reference To Separation Properties

This thesis is a study of abstract fuzzy convexity spaces and fuzzy topology fuzzy convexity spaces No attempt seems to have been made to develop a fuzzy convexity theoryin abstract situations. The purpose of this thesis is to introduce fuzzy convexity theory in abstract situations

Quantified set inversion with applications to control

This paper describes a new reliable method, based on modal interval analysis (MIA) and set inversion (SI) techniques, for the characterization of solution sets defined by quantified constraints satisfaction problems (QCSP) over continuous domains. The presented methodology, called quantified set inversion (QSI), can be used over a wide range of engineering problems involving uncertain nonlinear models. Finally, an application on parameter identification is presented