Network performance

During the training session the performance of the network must be monitored. Different performance criteria are possible, but usually the normalized standard error, NSE, is used. 

The NSE does give, however, a good general idea of the performance of the network and is therefore commonly used during the training session. In Fig. 44.15a a performance curve is shown. The NSE decreases monotonically with the number 

A typical performance behaviour is shown in Fig. 44.16b. The increase of the NSE for the monitoring set is a phenomenon that is called overtraining. This phenomenon can be compared to fitting a curve with a polynomial of a too high order or with a PCR or PLS model with too many latent variables. It is caused by the fact that after a certain number of iterations, the noise present in the training set is modelled by the network. The network acts then as a memory, able to recall 

In Fig. 44.16c the performance behaviour of a paralysed network is shown. The normal decrease of the NSE stops too soon and the NSE remains too high to be acceptable. The paralysation of the network occurs when the weighted input value, 

The performcuice behaviour shown in Fig. 44.16d is caused by the fact that the monitoring set and the training set represent different relationships or when some outliers are present in the monitoring set that are not present in the training set. 

Network congestion caused by simultaneous data flows from Pq Ps and Pi P7. The link from So S4 must be used by both traffic flows, limiting network performance. The use of Se by both traffic flows will not cause congestion because switching elements can handle multiple flows involving distinct links without performance loss. 

The application developer typically assumes that the network is flat and complete, that is, any given processing element has equal access to all others regardless of other network traffic. However, as we have seen in section 2.2.2, 

Average bandwidth obtained with adaptive and static routing, shown as a fraction of the peak bandwidth measured for each case. InfiniBand with 4x single data rate was used for static routing, and 10 Gigabit Ethernet was used for adaptive routing. Data were obtained on a Linux cluster and represent average measured bandwidths for the Sandia Cbench Rotate benchmark.  

As a first approximation, after the first word of data enters the network, the subsequent words are assumed to immediately follow as a steadily flowing stream of data. Thus, the time required to send data is the sum of the time needed for the first word of data to begin arriving at the destination (the latency, a) and the additional time that elapses until the last word arrives (the number of words times the inverse bandwidth, j8)  

The latency can be decomposed into several contributions the latency due to each endpoint in the communication, fendpoint the time needed to pass through each switching element, 4w and the time needed for the data to travel through the network links, funk thus, the latency can be expressed as 

---

Peh KK, Lim CP, Qwek SS, Khoti KH. Use of artificial networks to predict drug dissolution profiles and evaluation of network performance using similarity profile. Pharm Res 2000 17 1386-98. 

Modem intranets provide very high network performance, and as one might expect. Cabinet performance over such networks is excellent. Overall Cabinet performance... 

In many modeling techniques, the number of parameters is modified many times looking for a setting that provides the maximum predictive ability for the model. Techniques for variable selection and methods based on artificial neural networks perform an optimization, that is, they search for conditions able to provide the maximum predictive ability possible for a given sample subset. 

Fioletov, V.E., Labow, G.J., and McPeters, R.D. (1999) An Assessment of the World Ground-based Total Ozone Network Performance from the Comparison with Satellite Data, J. Geophys. Res., 104, pp. 1737-1747. 

Universitat Wurzburg Provides a software framework for rapid network assembly, network overview, and network performance analysis (http //www.bioinfo. biozentrum. uni - wuerzburg. de/c omputing/yana)... 

A certain amount of information has to be made available to the network which will be processed to obtain the output vector at the current time instant. The inputs can come either from direct measurements from the process, or from the network itself (i.e., NN outputs from previous time instants). The choice of the inputs should be made with engineering judgment. Too many inputs would overload the network and introduce unnecessary correlations among data, and can therefore disrupt the network performance on the other hands, too few inputs could be not enough for the network to learn the actual process behaviour. In Greaves et al. (2003), at time tk the following inputs were fed to the network tk, output vector Z0 at initial time (t0), and current values for the internal reflux and reboil ratios (Rd and RB, respectively), distillate rate (D), and bottoms rate (B). 

The latter result shows that to interpret the mechanical properties of networks we do not need to take into account the spatial inhomogeneities of crosslink distribution in a sample, at least in the rubbery state. The analysis of epoxy networks performed under the framework of a tree-like model and experiments 7,10-26) brought the... 

The fundamental idea behind training, for all neural network architectures, is this pick a set of weights (often randomly), apply the inputs to the network and see how the network performs with this set of weights. If it doesn t perform well, then modify the weights by some algorithm (specific to each architecture) and repeat the procedure. This iterative process is continued until some pre-specified stopping criterion has been reached. 

An important way to improve network performance is through the use of prior knowledge, which refers to information that one has about the desired form of the solution and which is additional to the information provided by the training data. Prior knowledge can be incorporated into the pre-processing and post-processing stages (Chapter 7), or into the network structure itself. 

By selectively changing sequences in E. coli translation initiation region with randomized calliper inputs and observing the corresponding neural network performance, Nair (1997) analyzed the importance of the initiation codon and the Shine-Dalgamo sequence. 

A provider network is a group of pharmacies that a health plan has contracted and from which members must choose when they have prescriptions filled. PBMs, insurers, and pharmacies themselves accomplish establishing and maintaining a network of pharmacy providers. For example, PBMs recruit pharmacies into a group, negotiate payment terms, and monitor and audit network performance. 

PQ of the network should cover loading tests as appropriate to verify network performance. Such testing is not always appropriate as PQ and may be included instead as part of ongoing performance monitoring. 

Screen refresh Data entry response times Serial communication interfaces Network performance Data storage capacity Multiple user access File and data integrity Shared file access... 

Network performance and outage (network and storage capacity utifization) Problems reported and resolved Help desk performance... 

Fl.l Are procedures or automated controls in place to monitor network performance and capacities including ... 

---