Exploring comprehensible classification rules from trained neural networks integrated with a time-varying binary particle swarm optimizer

Purpose

Extracting comprehensible classification rules is the most emphasized concept in data mining researches. In order to obtain accurate and comprehensible classification rules from databases, a new approach is proposed by combining advantages of artificial neural networks (ANN) and swarm intelligence.

Method

Artificial neural networks (ANNs) are a group of very powerful tools applied to prediction, classification and clustering in different domains. The main disadvantage of this general purpose tool is the difficulties in its interpretability and comprehensibility. In order to eliminate these disadvantages, a novel approach is developed to uncover and decode the information hidden in the black-box structure of ANNs. Therefore, in this paper a study on knowledge extraction from trained ANNs for classification problems is carried out. The proposed approach makes use of particle swarm optimization (PSO) algorithm to transform the behaviors of trained ANNs into accurate and comprehensible classification rules. Particle swarm optimization with time varying inertia weight and acceleration coefficients is designed to explore the best attribute-value combination via optimizing ANN output function.

Results

The weights hidden in trained ANNs turned into comprehensible classification rule set with higher testing accuracy rates compared to traditional rule based classifiers.     

Immune-based algorithms for dynamic optimization

The main problem with biologically inspired algorithms (like evolutionary algorithms or particle swarm optimization) when applied to dynamic optimization is to force their readiness for continuous search for new optima occurring in changing locations. Immune-based algorithm, being an instance of an algorithm that adapt by innovation seem to be a perfect candidate for continuous exploration of a search space. In this paper we describe various implementations of the immune principles and we compare these instantiations on complex environments.     

<Emphasis Type="Italic">New-Age</Emphasis>: A Negative Bias Temperature Instability-Estimation Framework for Microarchitectural Components

Degradation of device parameters over the lifetime of a system is emerging as a significant threat to system reliability. Among the aging mechanisms, wearout resulting from Negative Bias Temperature Instability (NBTI) is of particular concern in deep submicron technology generations. While there has been significant effort at the device and circuit level to model and characterize the impact of NBTI, the analysis of NBTI’s impact at the architectural level is still at its infancy. To facilitate architectural level aging analysis, a tool capable of evaluating NBTI vulnerabilities early in the design cycle has been developed that evaluates timing degradation due to NBTI. The tool includes workload-based temperature and performance degradation analysis across a variety of technologies and operating conditions, revealing a complex interplay between factors influencing NBTI timing degradation.     

Betriebsinformatik und Wirtschaftsinformatik als notwendige anwendungsbezogene Ergänzung einer allgemeinen Informatik – Vorschläge zur Verbesserung der akademischen Ausbildung auf dem Gebiet der automatisierten Datenverarbeitung in der Bundesrepublik Deutschland

Zusammenfassung  Nachdruck eines Aufsatzes aus elektronische datenverarbeitung 11(11)1969:544–548. This article is also available in English via and : Grochla E (2008) Corporate Information Systems Engineering and Business and Information Systems Engineering as a Necessary Application-Oriented Extension of General Computer Science – Proposals for Enhancing Academic Education in the Field of Automated Data Processing in the Federal Republic of Germany. Bus Inf Syst Eng. doi .

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An AP structure with Finslerian Flavor: Path equations

The Bazanski approach to deriving paths is applied to Finsler geometry. The approach is generalized and applied to a new developed geometry called “Absolute parallelism with Finslerian Flavor” (FAP). A set of path equations is derived for the FAP. It is a horizontal (h) set. A striking feature in this set is that the coefficient of the torsion term jumps by a step of one-half from one equation to the other. It is tempting to believe that the h-set admits some quantum features. Comparisons with the corresponding sets in other geometries are given. Conditions for reducing the set of path equations obtained to well-known path equations in some geometries are summarized in a schematic diagram.     

Internet-Based Control of Industrial Automation Systems

This paper presents a new method for Internet-based control of linear automation systems by combining the predictive control and the variable sampling period strategies. In this way, event driven sensors are implemented and the sensors are triggered to sample the outputs of the plant, when new control input signals are received by the actuators. Therefore, at each sampling instant, total control loop delay will be equal to the sampling period which is unknown. In order to deal with Internet effects, associated with a range of pre-specified time delays, appropriate zero-order hold discrete-time models of the Internet-based plant are calculated off-line, and based on them, some stabilizing control signals are constructed on-line. This control signals are then packed in the control-side packet, transmitted back to the plant-side and received by a time delay compensator module. According to the actually occurred time delay in the loop, this module selects a single entry of the received control vector for each actuator, and applies them to the plant, through zero-order hold elements. Simultaneously, the sensors are triggered to measure the new plant data, the plant-side packet is assembled and transmitted to the control-side. The above procedure is then repeated from start. A less conservative switched quadratic Lyapunov is used here for stabilizing controller design. Simulation studies on well-known benchmark problems demonstrate the effectiveness of the proposed method.     

A Minimal Closed-form Solution for the Perspective Three Orthogonal Angles (P3oA) Problem: Application To Visual Odometry

We provide a simple closed-form solution to the Perspective three orthogonal angles (P3oA) problem: given the projection of three orthogonal lines in a calibrated camera, find their 3D directions. Upon this solution, an algorithm for the estimation of the camera relative rotation between two frames is proposed. The key idea is to detect triplets of orthogonal lines in a hypothesize-and-test framework and use all of them to compute the camera rotation in a robust way. This approach is suitable for human-made environments where numerous groups of orthogonal lines exist. We evaluate the numerical stability of the P3oA solution and the estimation of the relative rotation with synthetic and real data, comparing our results to other state-of-the-art approaches.