The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a new approach to solving model externalization by taking into consideration the imprecise nature of decision makers' judgements on the different tacit models. Knowledge in the form of fuzzy rules are created using a neuro-fuzzy system called the Hypothalamic and Piagetian Fuzzy Inference System (HtPFIS). The structure of HtPFIS is inspired from the simplified neuronal circuitries...
In this paper, a robust adaptive fuzzy control for a class of nonlinear uncertain systems preceded by an unknown dead-zone and with unknown upper bound of uncertainties is developed. The dead-zones are quite commonly encountered in many systems (e.g., DC servosystem, robot, and machine tools), are usually poorly known, and may severely limit the performance of control. In addition, the system uncertainties...
The strength of neuro-fuzzy systems involves two contradictory requirements in neuro-fuzzy modeling: interpretability versus accuracy. The Yager-inference-scheme-based fuzzy CMAC (FCMAC-Yager) architecture shows advantages such as it exhibits learning and memory capabilities of the human cerebellum through the CMAC (cerebellar model articulation controller) structure and the human way of reasoning...
This research proposes the application of NTC (neural text categorizer) for categorizing news articles. Even if the research on text categorization has been progressed very much, documents should be still encoded into numerical vectors. Encoding so causes the two main problems: huge dimensionality and sparse distribution. The idea of this research as the solution to the problems is to encode documents...
The existence of many pattern recognition systems (PRSs) and their relative merits and drawbacks highlights the need for a metalearning framework that can find the best PRS method for a given task. To address this issue, a hyperparameter evolutionary optimization (HPEO) framework was previously devised, initially using a genetic algorithm to tune external PRS parameters in a modular fashion, decoupled...
Optimization methods have been developed by many researchers. Especially, the methods based on evolutionary algorithms (EAs) have received increased attention from diversity fields. Recently, bacterial foraging algorithm mimicked bacterial behavior has been introduced by Passino. However, his work did not implement an important bacterial behavior regulating division so-called dasiaquorum-sensingpsila...
We take into account the problem of extending the univariate marginal distribution genetic algorithm (UMDGA) modeling and analysis to the multivariate framework. In particular, we introduce the basic general concepts and mathematical formalism to devise genetic algorithms useful to solve problems involving dependencies among genes. We state the relationships between the natural component attractors...
Hypernetworks are a weighted hypergraph where evolutionary methods are learning the model structure and parameters. The evolutionary methods enable the hypernetwork model to conserve significant features implicitly during the learning process. In this study, we propose a novel feature selection method based on occurrence frequencies of attributes in hyperedges by analyzing the structure of a hypernetwork...
Evolutionary hypernetworks (EHNs) are recently introduced models for learning higher-order probabilistic relations of data by an evolutionary self-organizing process. We present a method that enables EHNs to learn and generate music from examples. Short-term and long-term sequential patterns can be extracted and combined to generate music with various styles by our method. Based on a music corpus...
Fuzzy and neuro-fuzzy systems are increasingly among the key technologies employed in many real-world applications. However, traditional neuro-fuzzy systems are generally still lacking the scalability traits required in the face of large-scale data and the capability to incorporate new information without catastrophically disrupting the existing knowledge base. This work aims at addressing these issues...
This paper presents an artificial fish swarm algorithm for solving Steiner tree problem. A novel encoding method of avoiding the loop generation for artificial fish representation of tree-structure and the operator of behaviors of artificial fish for searching optimal solution of Steiner tree problem are proposed. Simulation experiments have been carried out on different network topologies for networks...
This paper presents a Ideal Analytic Hierarchy Process which can provide an overall assessment of system performance. To obtain a unified index, this paper presents the scaled performance of each item, and propose the use of the AHP model with three states: [Ideal] - [Actual] - [Possible] states. By calculating eigenvalues of states, the unified index can be obtained. The proposed method is applied...
Load balancing in parallel master-slave implementations on heterogeneous computing clusters is a pressing research problem. Proper load balancing can lead to dramatic speedups in program run times. This paper introduces a novel adaptive fuzzy load balancer which automatically senses cluster state through measurements of node evaluation times and network delays. Measured data are collected within a...
Fuzzy rules generated from neuro-fuzzy systems may contain ambiguous rules, due to numerous factors. While contradiction-correction often ensures consistency in fuzzy rule-bases, a differing approach should be reserved for problems where the linguistic definitions can be mutually-inclusive. For these cases, the proposed ambiguity-correction approach is a simple procedure that prevents excessive skew...
The hybrid neural fuzzy inference system (Hy-FIS) is a five layers adaptive neural fuzzy inference system, based on the compositional rule of inference (CRI) scheme, for building and optimizing fuzzy models. To provide the HyFIS architecture with a firmer and more intuitive logical framework that emulates the human reasoning and decision-making mechanism, the fuzzy Yager inference scheme, together...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.