Mini Symposium 2012        

   September 4, 2012

Óbuda University, Budapest, Hungary

Recent Advances in Intelligent Engineering


Óbuda University

Address: Bécsi út 96/B, H-1034 Budapest, Hungary

Final Program

9:00 - 11:102012 Honorary Professors' Talks

9:00 - 9:20Prof. Dr. James M. Tien: Towards The Next Industrial Revolution

The outputs or products of an economy can be divided into services products and goods products (due to manufacturing, construction, agriculture and mining). To date, the services and goods products have, for the most part, been separately mass produced. However, in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods, the next – or third – industrial revolution is focused on the integration of services and/or goods; it is beginning in this second decade of the 21st Century. The Third Industrial Revolution (TIR) is based on the confluence of three major technological enablers (i.e., big data analytics, adaptive services and digital manufacturing); they underpin the integration or mass customization of services and/or goods. As detailed in an earlier paper, we regard mass customization as the simultaneous and real-time management of supply and demand chains, based on a taxonomy that can be defined in terms of its underpinning component and management foci. The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced – as “servgoods” – in real-time, resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers.

9:20 - 9:40Prof. Dr. Mo M. Jamshidi: Sustainable Energy Systems: Cyber-Physical Based Intelligent Mangement of Micro-Grids

Sustainable energy has slowly but surely becoming relevant source of energy in many parts of the world. From US to Europe to Asia and South Pacific and on to Middle East, photovoltaic and wind energies are the desired sources. Such new and expanded sources of energy is fast creating numerous sources of distributed generations and creating a great number of micro-grids of energy. However, intermittency nature of both of these sources would make it very difficult to rely on for instantaneous need for electricity in urban or rural areas.
In this presentation, fundamental aspects of cyber-physical systems will first be discussed and then a management scheme for microgrids will be presented based on a Fuzzy Logic-based framework is proposed for control of Battery Storage Unit in Micro-Grid Systems to achieve Efficient Energy Management. Typically, a Micro-Grid system operates synchronously with the main grid and also has the ability to operate independently from the main power grid in an islanded mode. Distributed renewable energy generators including solar, wind in association with batteries and main grid supply power to the consumer in the Micro-Grid network. The goal here is to control the amount of power delivered to/taken from the storage unit in order to improve a cost function, defined based on summation of payment required for purchasing power from main grid or profit obtained by selling power to the main grid and distribution power loss, through reasonable decision making using predetermined human reasoning-based fuzzy rules. Profiles of system variables such as Consumer’s Load Demand, Electricity Price Rate, and Renewable Electricity Generation Rate are assumed arbitrarily for obtaining general results. Measures of payment/profit will be extracted to compute amounts of cost and balance for the network which represents benefits of using Fuzzy logic for Storage Unit control with and without considering storage unit capacity limits. Simulation results are presented and discussed.

9:40 - 10:00Prof. Dr. Keith W. Hipel: Responsible Governance in a Complex World: A System of Systems Engineering Design

An integrative and adaptive design for Responsible Governance is put forward for addressing large-scale complex problems facing society based on a System of Systems (SoS) Engineering framework that reflects the values of stakeholders using a participatory approach and achieves desirable systems goals such as resilience, sustainability and fairness. To demonstrate that this can actually be accomplished in practice, Singapore is employed as a remarkable example in which the nation was purposefully designed according to sound Systems Engineering principles resulting in a highly respected country that brings prosperity, fairness and fulfillment to its citizens and serves as a beacon of hope for other countries to emulate. In contrast to Singapore’s success, a range of tough interconnected systems problems are described for which systems solutions are urgently needed: the failed American financial system, unfair medical systems, unreliable aging infrastructure, self-induced climate change, preparing for extreme weather conditions like hurricane Katrina, fair trade and the electrical system collapse in North America. As is explained, the underlying cause for underperformance or system collapse in these large-scale problems is a faulty value system. Accordingly, ethical system values reflecting the values system of stakeholders, including nature and future generations, constitute the solid foundations upon which Responsible Governance is constructed. Extensive research is urgently needed for developing a comprehensive theoretical structure for System of Systems Engineering for suitably solving current and emerging complex systems problems.

10:00 - 10:30coffee break

10:30 - 10:50Prof. Dr. Tom D. Gedeon: Bio-inspired Computing for Human-centred Computing

Human-centred computing can be defined as supporting our goals and interests rather than the tasks we need to do, or defined as being about advanced natural interfaces which are easy to use and respond and predict our actions much as other people do. In this talk I focus mostly on the former in the realm of generating art and modeling esthetic selection, with the use of two bio-inspired computing techniques, evolutionary algorithms and neural networks.

10:50 - 11:10Prof. Dr. Sam Kwong: Evolutionary Multi-objective Optimization with Hybervolume and Adaptive Operators

Nowadays, many real world problems are multi-objective in nature in the sense that multiple conflicting criteria need to be optimized simultaneously. As a consequence, instead of a global optimal solution in the case of single-objective optimization, usually, the optimum of multi-objective optimization corresponds to a set of so called Pareto optimal solutions for which no solutions can win in all objectives, due to the conflict between objectives. Evolutionary Multi-objective Optimization (EMO) algorithms have been widely used in practice for solving these multi-objective optimization problems for several reasons. At first, EMO approaches can tackle problems with nonlinear, non-differentiable, or noisy objective functions. Secondly, the population based search manner opens new opportunities in dealing with multi-objective optimization problems by searching for multiple alternatives simultaneously. Therefore, EMO has become one of the most active research areas in evolutionary computation. In this talk, I will first give an in--depth introduction to the EMO field and subsequently presented two of our recent developments which are 1) the hypervolume based technique and 2) adaptive operator algorithms.

11:10 - 11:30IEEE SMC Distinguised Lecturere Program Talk

Prof. Dr. C. L. Philip Chen: Fuzzy Multi-Attribute Decision Making Algorithm for Vehicle Navigation in Sensor Network Environments

In a large-scale wireless sensor traffic network, collecting and processing of the global real-time traffic information are often unreliable. Making real-time navigation decision becomes an arduous task. The vehicle navigation here is considered as a multi-attribute decision making (MADM) problem. To address this issue, an efficient Wireless-Sensor-Network-based real-time vehicle navigation algorithm is proposed, in which multiple local traffic information are considered to make navigation decision in a quick and accurate way.
Because the real-time traffic information involved in the navigation decision making should not be all denoted by exact data, some of them are more suitable to be denoted by fuzzy data, a general distance metric is presented for the processing of both exact and fuzzy data in MADM. The proposed algorithm can provide various navigation decisions according to the choice of different attributes to meet the diverse navigation requirements of drivers. Simulation results show the suitability and efficiency of the proposed algorithm.

11:45 - 13:15Reception
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Óbuda University 2012