The hidden dimension of the urban morphology is underlying morphological rules system. number these has increased and their application tends to become more complex. morphosis based digital approaches widespread. However, achieving target values for all difficult. This impacts social, environmental aesthetic objectives rules. paper proposes a classification assist form. aim endow system with hi...

This paper devises a scheme which can discover the state association rules of process object. The scheme aims to dig the hidden close relationships of different links in process object. We adopt a method based on difference and extremum to compute the timing. Clustering is used to classifying the adjusted data, and the next is associating the clusters. Based on the rules of clusters, we produce...

This study uses fractal analysis to measure the detailed intensity of well-known Classical and Renaissance façades. The develops a method understand their interrelated design principles more comprehensively. With this evaluation tool, one can observe intrinsic connections that support historical continuity point out balancing composition protocols, such as ‘compensation rule’, regulated for cen...

In this paper, we study the scalar-diquark–scalar-diquark–antiquark-type [Formula: see text] pentaquark state with QCD sum rules, predicted mass is in excellent agreement experimental data from LHCb collaboration, and supports assigning to be hidden-charm spin-parity text]. We take into account flavor mass-breaking effect, estimate spectrum of diquark–diquark–antiquark-type states strangeness

An effective algorithm for extracting M-of-N rules from trained feedforward neural networks is proposed. Two components of the algorithm distinguish our method from previously proposed algorithms which extract symbolic rules from neural networks. First, we train a network where each input of the data can only have one of the two possible values, -1 or one. Second, we apply the hyperbolic tangen...

This paper describes the design and implementation of a phonological modeling system based on autosegmental and articulatory phonology and its application in speech recognition. Pronunciation modeling is an integral part in speech recognition systems. Together with language modeling, signal processing and learning models (e.g. Hidden Markov model and neural network model), it innuences the perf...

This paper proposes a new method for the extraction of knowledge from a trained type feed-forward neural network. The new knowledge extracted is expressed by fuzzy rules directly from a sensibility analysis between the inputs and outputs of the relationship that model the neural network. This easy method of extraction is based on the similarity of a fuzzy set with the derivative of the tangent ...

This paper proposes an algorithm to infer the maneuver intention of obstacle ship and check its compliance with maritime traffic rules avoid collision ensure safety. A probabilistic graphical model is constructed represent relationship between motion observations hidden comply rules. The belief ship's modeled quantified using tools such as dynamic Bayesian networks. Three different intent infer...