A knowledge-based clustering scheme

In this paper the notion of conceptual cohesiveness is precised and used to group objects semantically, based on a knowledge structure called ‘cohesion forest’. A set of axioms is proposed which should be satisfied to make the generated clusters meaningful.

Australian innovation ecosystem: A critical review of the national innovation support mechanisms

Innovation is understood as the combination of existing ideas or the generation of new ideas into new processes, products and services, and widely viewed as the main driver of growth in contemporary economies. In the age of the knowledge economy, successful economic development is intimately linked to a country’s capacity to generate, acquire, absorb, disseminate, and apply innovation towards advanced technology products and services. This development approach is labelled as knowledge-based economic development and highly associated with a capacity embodied in a country’s national innovation ecosystem. The research reported in this paper aims to critically review the Australian innovation ecosystem in order to provide a better understanding on the potential impacts of policy and support mechanisms on the innovation and knowledge generation capacity. The investigation places Australia’s innovation system and national-level innovation support mechanisms under the microscope. The methodology of the study is twofold. Firstly, it undertakes a critical review of the literature and government policy documents to better understand the innovation policy and support mechanisms in the country. It, then, conducts a survey to capture Australian innovation companies’ perceptions on the role and effectiveness of the existing innovation incentive programs. The paper concludes with a discussion on the key insights and findings and potential policy and support directions of the country to achieve a flourishing knowledge economy.

A knowledge-based approach to pattern generation

Pattern Cognition is looked at from the functional view point. The need for knowledge in synthesizing such patterns is explained and various aspects of knowledge-based pattern generation are highlighted. This approach to the generation of patterns is detailed with a concrete example.

Knowledge-based clustering

In the knowledge-based clustering approaches reported in the literature, explicit know ledge, typically in the form of a set of concepts, is used in computing similarity or conceptual cohesiveness between objects and in grouping them. We propose a knowledge-based clustering approach in which the domain knowledge is also used in the pattern representation phase of clustering. We argue that such a knowledge-based pattern representation scheme reduces the complexity of similarity computation and grouping phases. We present a knowledge-based clustering algorithm for grouping hooks in a library.

Representation of evidence: An approach to uncertainty handling in knowledge-based systems

Many knowledge based systems (KBS) transform a situation information into an appropriate decision using an in built knowledge base. As the knowledge in real world situation is often uncertain, the degree of truth of a proposition provides a measure of uncertainty in the underlying knowledge. This uncertainty can be evaluated by collecting `evidence' about the truth or falsehood of the proposition from multiple sources. In this paper we propose a simple framework for representing uncertainty in using the notion of an evidence space.

Knowledge-Based Approach Using Support Vector Machine for Transmission Line Distance Relay Co-ordination

In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.