An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour in consensus reaching process under social network group decision making is proposed, which is based on a theoretically sound optimal feedback model. The manipulation behaviour classification is twofold: (1) ‘individual manipulation’ where each expert manipulates his/her own behaviour to achieve higher importance degree (weight); and (2) ‘group manipulation’ where a group of experts force inconsistent experts to adopt specific recommendation advices obtained via the use of fixed feedback parameter. To counteract ‘individual manipulation’, a behavioural weights assignment method modelling sequential attitude ranging from ‘dictatorship’ to ‘democracy’ is developed, and then a reasonable policy for group minimum adjustment cost is established to assign appropriate weights to experts. To prevent ‘group manipulation’, an optimal feedback model with objective function the individual adjustments cost and constraints related to the threshold of group consensus is investigated. This approach allows the inconsistent experts to balance group consensus and adjustment cost, which enhances their willingness to adopt the recommendation advices and consequently the group reaching consensus on the decision making problem at hand. A numerical example is presented to illustrate and verify the proposed optimal feedback model

Advanced channel coding for space mission telecommand links

We investigate and compare different options for updating the error correcting code currently used in space mission telecommand links. Taking as a reference the solutions recently emerged as the most promising ones, based on Low-Density Parity-Check codes, we explore the behavior of alternative schemes, based on parallel concatenated turbo codes and soft-decision decoded BCH codes. Our analysis shows that these further options can offer similar or even better performance.Comment: 5 pages, 7 figures, presented at IEEE VTC 2013 Fall, Las Vegas, USA, Sep. 2013 Proc. IEEE Vehicular Technology Conference (VTC 2013 Fall), ISBN 978-1-6185-9, Las Vegas, USA, Sep. 201

An intelligent system for risk classification of stock investment projects

The proposed paper demonstrates that a hybrid fuzzy neural network can serve as a risk classifier of stock investment projects. The training algorithm for the regular part of the network is based on bidirectional incremental evolution proving more efficient than direct evolution. The approach is compared with other crisp and soft investment appraisal and trading techniques, while building a multimodel domain representation for an intelligent decision support system. Thus the advantages of each model are utilised while looking at the investment problem from different perspectives. The empirical results are based on UK companies traded on the London Stock Exchange

New Modes of Governance in Europe: Policy Making without Legislating? IHS Political Science Series: 2002, No. 81

The article analyzes new modes of governance in Europe. Firstly, different types of new governance, the open coordination method and voluntary accords, and their individual elements are identified. The theoretical discussion about them points out the reasons of their emergence, their mode of operation and the links to the ‘classical’ forms of decision-making. Secondly the simple question of the relative importance of new modes of governance in European policy-making is raised. Looking at the policy measures from the beginning of 2000 until July 2001, the analysis found that only a minority of measures can be considered new modes of governance, defined in the above terms. A third question raised concerns political institutional capacity. Finally the question or instrumental capacity or effectiveness is raised