Experts networks

The Drought Management Plan Report written by the Water Scarcity and Droughts Expert Network (November 2007) recommends Development of DSS for the best exploitation of aU information available, including drought forecasts, to optimize... 

In a mixture-of-experts model (Jacobs et al., 1991), different expert networks were assigned to tackle sub-tasks of training cases, and an extra gating network was used to decide which of the experts should determine the output. The model discovered a suitable decomposition of the input space as part of the learning process. Later the model was further extended (Jordan Jacobs, 1994) into a hierarchical system with a tree structure. In molecular applications, cascaded networks-where outputs of some networks become the inputs of others-were used to improve performance (Rost Sander, 1994). Multiple neural network modules may run in parallel in order to scale up the system (Wu et al., 1995). More than one network can also be used to extract different (e.g., local vs. global) features (Mahadevan Ghosh, 1994). 

Caudill, M. Expert networks. In Neural Network PC Tools Academic Press New York, 1990 189-214. 

Abstract. Since the credibility of the information on food safety is very important, the methods how to disseminate verified data on chemical food contaminants to whom it may concern is the SAFEFFOODNET project s principal objective. The Safefoodnet research project connects independent research institutions, universities, government agencies and ministries from across the EU. The objective is to harmonize and integrate the infrastructure and activities of the NMS and ACC in the field of chemical food safety with those of Old Member States and to provide the recently established European Food Safety Authority with an expert network in the field of chemical food safety. The structure of the general work plan has been broken down into 5 work packages (WP) to respond in a practical way to the SAFEFOODNET proposed objectives. 

The ICCIDD consists of a multidisciplinary global expert network of over 700 professionals from more than 100 countries with an official relationship with the WHO. 

Based on experience, this situation is absolutely typical of the way in which synthetic polymer chemists operate in an industrial setting, being integrated constantly in interdisciplinary expert networks, all parts of which have their own competencies, and which are all inter-dependent. Clearly, without a team, a single polymer chemist cannot do anything - but the others won t be able to work without him or her, either ... 

You should be aware that ANNs and ESs can be combined into expert networks. This often requires the use of fuzzy arithmetic and logic (see Chapter 9 of Ref. 62 for an introduction). So when should you use an ANN as opposed to an ES or statistical method Only you can provide the answer. We have presented a variety of issues to consider when making a choice. Howevei you are most famihar with your data and therefore best equipped to consider the issues involved in deciding. In the final analysis, if you are looking for the best answers to your problems, you may need to try several methods to see which one in fact performs best for you. 

Close liaison between Porton s scientists and expert networks elsewhere in Britain and overseas, essential in maintaining a first-class research facility, was to be assured through the Chemical Warfare Committee, which was broadly representative of the wider scientific, military, and business community. To ensure the coordinated production of toxic agents, including those for testing purposes at Porton, the committee recommended the creation of a state-controlled factory for chemical warfare products at Sutton Oak, near St Helens in Lancashire, which later became the Chemical Defence Research Establishment. A representative of Porton liaised with members of the committee about planned field trials. It was this coordinated approach to chemical warfare through an external body of experts and stakeholders that other nations, the United States and Canada especially, began to emulate. 

The Mixture of Experts (ME) network developed by Jacobs and Jordan (1991) was adopted in this work. The ME architecture consists of a set of ik expert networks and one gating network (Fig. 1). The task of each expert i is to approximate a function x->y over a region of the input space. The task of the gating network is to assign an expert network to each input vector x. The final output y is a linear combination of the expert networks. The interesting property of this network is that it is able to learn to partition a task into two or more functionally independent tasks and to allocate distinct networks to learn each task. 

Figure 1. Block diagram of a mixture of experts network the outputs of the expert networks are mediated by a gating network.

The expert outputs y, correspond in this case to the conditional mean of the desired response d given the input vector x and that the ith expert network is used, y, = [P(d x,i)]- The outputs of the gating networks gi are interpreted as the conditional probability P(i x) of picking the expert i given de input x. The probability of the desired target given the input x is thus... 

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