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	Predictive modelling - Wikipedia, the free encyclopedia
		Predictive modelling is the process by which a model is created or chosen to try to best predict the probability of an outcome.
		In many cases the model is chosen on the basis of detection theory to try to guess the probability of a signal given a set amount of input data, for example given an email determining how likely that it is spam.
		In biostatistics, the researcher may be interested in trying to model the probability of a patient being diagnosed with a certain type of cancer based on knowing, say, the incidence of that cancer in his or her family.
	en.wikipedia.org /wiki/Predictive_modelling (306 words)

	Archaeological Predictive Modelling - Methodology
		Predictive modelling is presented as a three stage process.
		Predictive modelling for archaeology is defined as a
		Predictive modelling became the subject of much research, but its role in settlement pattern research diminished as it was applied more and more as a cultural resource management tool.
	modelling.pictographics.com /method.htm (3644 words)

	ISFHT - Hygiene Review 1997 - SHAPING FOOD SAFETY AND QUALITY
		Predictive models need to be used with full appreciation of how they have been constructed and the potential pitfalls.
		The majority of commercially available models have been thoroughly validated and a knowledge of the validation and reliability of models when used for particular purposes is an important aspect of their use and application.
		Predictive models also have a role to play in education in that they allow simple demonstration of microbial behaviour and risk without the need for expensive laboratory exercises.
	www.sofht.co.uk /isfht/irish_97_predictivemodeling.htm (1973 words)

	Predictive modelling
		The development of predictive models will contribute to a better understanding of factors and processes structuring the distribution of marine habitats.
		Develop a habitat prediction model from the relationships between the environmental factors and the distribution of selected biological communities.
		The initial maps that result from the predictive modelling will be refined through testing the predictive capability with real biological data and where appropriate with the newly acquired data from Action 3.
	www.jncc.gov.uk /page-1626 (607 words)

	Predictive Modelling - Fact Sheet No. T-09 - Publications - Defence R&D Canada – Toronto
		Prediction of human response in such environments is essential to both operational and contingency planning.
		Diving: Correlation between the predicted bubble size using DRDC Toronto's Bubble Evolution Model with the range of occurrence of decompression sickness in three divers, for a repetitive dive to 25 metres of seawater (msw).
		Airborne contamination: The COHb (carboxyhemo-globin) Prediction Model was developed to forecast the risk of carbon monoxide (CO) toxicity in hazardous environmental atmospheres (e.g., from the discharge of weapons firing).
	www.toronto.drdc-rddc.gc.ca /publications/factsheets/t09_e.html (453 words)

	Predictive Modelling/Algorithm Assimilation - Cormon Corrosion Monitoring Limited
		Predictive modelling tools for corrosivity and scale/deposit pipeline profiling, continue to develop and improve.
		The performance of the model itself can be critical to looking forward into the future to predict risk to the asset and the prevailing trends.
		Empirical model constants may be adjusted to optimise the model to match the system outputs.
	www.cormon.com /flow/predictive_modelling.aspx (237 words)

	Researchers develop predictive protein method (Site not responding. Last check: 2007-11-03)
		Predictive modelling is a new approach to drug discovery that takes information from lab analysis and concentrates it in predictive models that may be evaluated on a computer.The new multi-scale protein modelling approach may have implications for an array of biotechnology applications, including bioprocessing and proteomics.
		The modelling technique is based on methods previously developed by the same researchers, from the Rensselaer Polytechnic Institute, for predicting the efficacy and side effects of small drug-like molecules.
		In tests performed by the scientists, the newly developed model successfully predicted the amount of a protein that binds to a material under a range of conditions by using molecular information obtained from the protein structure.
	www.drugresearcher.com /news/printNewsBis.asp?id=62108 (358 words)

	Predictive capacity without explanatory capacity is worthless (Site not responding. Last check: 2007-11-03)
		Predictive models are tools for projecting known patterns or relationships into unknown times or places.
		Frequently, GIS is utilized in site predictive modelling to maximize the efficiency and return of subsequent field survey.
		The approach presented in this paper differs from standard predictive models in that the goal is not to locate where most of the sites will be most of the time, but rather to predict the location of those unique sites that do not cluster around specific environmental variables.
	oregonstate.edu /~carlislk (1887 words)

	Model solutions? The status of materials modelling
		Further, the extensions of accelerator methods to non-nuclear industry (like the ion implantation of semiconductors) triggered the modelling of systems in which there are large concentration gradients and where there may be electronic excitation.
		But modelling doesn't depend only on the science: there are constraints from the time and funds available, and from the view as to what is a solution.
		The model (by I S Doltsinis, J H Harding, M Marchese 1998 Arch Comp Meth in Eng 5 59) modelled all the stages of these processes, including the themal and mechanical properties of the product film; they also developed genetic algorithm tools to optimise operating conditions for chosen properties.
	www.europhysicsnews.com /full/07/article5/article5.html (2413 words)

	AusRivAS Physical and Chemical Assessment Module: Appendices (continued) (Site not responding. Last check: 2007-11-03)
		Habitat Predictive Modelling has the ability to incorporate a range of physical and chemical variables collected at different scales, as well as variables that are specifically important to macroinvertebrates.
		Merging the hierarchical approaches of Habitat Predictive Modelling and River Styles has the potential to improve prediction of stream habitat features by encompassing the scales that represent geomorphological processes, as well as the scales that represent aspects of the physical environment that are important for macroinvertebrates.
		The robustness and power of a predictive model based solely on physical characteristics is directly dependent on the variables that are available to construct the models, and on the physical processes that these variables indicate.
	www.deh.gov.au /water/rivers/nrhp/protocol-3/chapter4d.html (2839 words)

	Healthcare Market Review
		As a result, traditional strategies of managing healthcare costs are increasingly being supplemented with the use of predictive models by a diverse range of organisations from the federal government to private employers.
		Predictive models can be population based or medical condition based.
		Predictive models use the same basic information with the addition of utilisation data which are coded by types, amount of services provided and/or diagnoses data consistent with the International Classification of Diseases (ICD9) format.
	www.watsonwyatt.com /europe/pubs/healthcare/render2.asp?ID=12064 (912 words)

	Predictive modelling algorithms for meta-analysis of individual patient data. (Site not responding. Last check: 2007-11-03)
		Predictive modelling algorithms for meta-analysis of individual patient data.
		Cox models with four predictive factors (age, disease state, CD4 cell count and hemoglobin levels) were used to estimate predicted individual hazards both for single trials and for various MIPD modeling methods (simple pooling, adjusted for study, stratified per study, fixed and random effects for predictors).
		Predictive modeling can be a major strength of MIPD, when performed and interpreted with standardized approaches.
	gateway.nlm.nih.gov /MeetingAbstracts/102272951.html (335 words)

	harpo (Site not responding. Last check: 2007-11-03)
		Predictive models of historic and prehistoric settlement are used in the Process to determine site potential for the area in question.
		To create the predictive model, the base coverages of land use/land cover, elevation, SPOT imaging, geology faults, streams, ancient and modern roads, and known Celtic hillforts were manipulated and combined to produce a probability map (that also takes a very long time to load).
		The application they use is "Erosion models and Iron Age Agricultural Intensification." They use GIS in their project to create 13 environmental variables from base layers using a number of GIS operations, transformations, and manipulations.
	www.cast.uark.edu /local/uaclasses/rast/spring98/rast16/harpo.html (2137 words)

	Legion - News (Site not responding. Last check: 2007-11-03)
		Predictive modelling by dynamic simulation helps to reduce uncertainty and avoid making false assumptions that might invalidate risk calculations.
		For example, modelling of situations such as the pedestrian thoroughfares at the Sydney Olympic Park helped the organisers resolve serious potential problems of crowding and evacuation at peak periods.
		The model is now being applied at several London Underground stations, the Cross Rail Project, the Athens 2004 Olympics and the commuter rail system in Hong Kong.
	www.legion.biz /news/article1.html (1432 words)

	4Thought neural network analysis software - salesforce modelling example
		In this example a model is built to estimate the sales value of each county, based on factors such as the population density and the number of retailers per capita in that region.
		Using state-of-the-art mathematical modelling techniques, 4Thought identifies patterns in data, representing a big advance over standard statistical techniques because it can identify what is a real pattern and what is just a pure coincidence.
		Combining the broad-pattern-to-fine-detail approach with constant monitoring of predictive ability, 4Thought identifies exactly when the most information has been drawn out of a set of data, and thus when to quit while the going is good.
	www.tech4t.com /pages/4thought_ch2.html (956 words)

	SSP&A Model Research (Site not responding. Last check: 2007-11-03)
		Inherent in the model calibration data set is information on the uncertainty associated with model predictions upon which environmental management is based.
		The ability to quantify uncertainty associated with key model predictions allows managers to optimize data gathering strategies on the premise that the best new data is that which most reduces the uncertainty associated with these predictions.
		Quantification of model predictive uncertainty forms a better basis for negotiation between environmental stakeholder groups than illusory certainty produced as an outcome of typical modeling practice.
	www.sspa.com /modelres/index.htm (554 words)

	Review of Physical River Assessment Methods - A Biological Perspective: Chapter 2 (continued) (Site not responding. Last check: 2007-11-03)
		The habitat features predicted to occur at a test site are compared against the habitat features that were actually observed at the test site, with the difference between the two being an indication of habitat condition.
		Habitat Predictive Modelling is based on the observation that stream systems are organised hierarchically (de Boer, 1992) and that there is a top down control on the expression of habitat features.
		Habitat Predictive Modelling assesses stream condition by comparing the local-scale habitat features predicted to occur at a site in the absence of degradation, against the features that were actually observed at a site.
	www.deh.gov.au /water/rivers/nrhp/protocol-2/chapter2f.html (1148 words)

	Archaeological Predictive Modeling: The Basic Ideas (Site not responding. Last check: 2007-11-03)
		Predictive archaeology in Trentino The objective of this study is a map for determining areas of archaeological risk in Trentino (in Italian).
		The model was then further evaluated by two field seasons of systematic survey and the model was updated to include the new data.
		They state that there are three main assumptions for statistical tests that have been ignored in archaeological predictive modeling: data collection/sampling integrity, a well established relationship between the sites and the variable used to predict their location, and complete independence of each variable including the uniqueness of its affect on site location.
	www.cast.uark.edu /~kkvamme/mnmodel/mnmodel.htm (6254 words)

	Cognos 4Thought neural network software for data analysis, predictive modelling, forecasting, response modelling...
		Once the inter-relationships between all of the different factors and volume is established, the resulting model can be used for both producing realistic forecasts of known predictive ability, and to look at the isolated effect of each individual factor.
		In either case, a model is built of whether or not the prospect is a respondent/customer, using those factors associated with each record, (typically geo-demographic details, and type and number of previous purchases).
		Similar models can be used to identify key drivers, quantify the effect of change and impact of local advertising, discover regional price sensitivities, or benchmark performance of different channels and media, while taking regional differences into account.
	www.tech4t.com /pages/4thought.html (1573 words)

	SAS adds predictive modelling capabilities to leading human capital management solution
		Organisations are now able to accurately predict which employees are most likely to resign voluntarily, allowing them to introduce intervention strategies key staff, as well as address the cost and competitive issues associated with employee turnover.
		New predictive modelling functionality enables businesses to address challenges such as voluntary employee turnover of key personnel and the associated effect on diversity in the organisation.
		Since staff turnover has a very large direct and indirect impact on costs, for instance recruitment and training costs as well as potential loss of crucial knowledge and skills, it is important that companies understand why turnover is happening and how and where it's directly impacting the organisation.
	www.itweb.co.za /office/sas/0402240805.htm (805 words)

	Predictive modelling optimises spares inventories: News from Clockwork Solutions
		Spar is a software modelling building platform used to build asset models for prediction and management of the performance and life cycle costs of complex systems.
		Spar technology uses Monte Carlo simulation to build highly accurate reliability-based asset models, and Sparopt provides an automatic optimisation capability for planning the number and timing of spare parts in the maintenance process.
		Any kind of model element can now be stored in and removed from multilevel storages at any point in time.
	www.engineeringtalk.com /news/clo/clo100.html (538 words)

	4Thought predictive modelling software - demand forecasting example - UK
		This example shows how the neural net approach can be used to model a business which is at the mercy of macro-economic rather than market forces.
		One factor which was thought to drive demand was the general health of the economy—whether it was booming or receding.
		This is because wholesalers have to compete with their own suppliers—when interest rates are low, customers tend to buy in bulk from a manufacturer rather than in small quantities from a wholesaler.
	www.tech4t.co.uk /pages/4thought_ch1.html (475 words)

	Predictive Modelling of Coal Flow (via CobWeb/3.1 planetlab2.cs.unc.edu) (Site not responding. Last check: 2007-11-03)
		The transfer chute at DBCT was used as a model for the study.
		This system was modelled using discrete element modelling (DEM), a computational technique that treats granular material as a collection of 2D or 3D rigid particles.
		DEM uses properties of the coal such as stiffness, damping and friction coefficients and cohesion/adhesion levels, as well as boundary conditions and the geometry of the transfer chute, and then calculates the forces on individual elements due to contact with walls and other elements of the flow.
	www.qcif.edu.au.cob-web.org:8888 /industry/Prime.htm (587 words)

	Internet Archaeol. 20. Ebert. Summary (via CobWeb/3.1 planetlab2.cs.unc.edu) (Site not responding. Last check: 2007-11-03)
		One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites.
		This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling.
		The temporal models thus created are then compared to a traditional predictive model.
	intarch.ac.uk.cob-web.org:8888 /journal/issue20/ebert_index.html (136 words)

	Measuring Gold Against Stocks In Predictive Modelling
		The purpose of this essay is to further define what we have already learned about the harmonics in the gold complex to formulate predictive models utilizing Fibonacci principles.
		For most in our modern day society, the proposition has not entered their minds as of yet, at least not in a serious way, as participation levels as a measure against the total investment universe are at historically low levels, and are likely to remain there for the entire initial stage of the bull market.
		Therefore, it should be understood that as participation levels in the precious metals markets increase, modelling parameters will change, volatility and scale will expand, and we intend to mark those changes as the bull matures in an understandable fashion.
	www.gold-eagle.com /editorials_03/captainhook071803.html (2469 words)

	Buyers' Guide
		Over-hyped technologies are supported by a large number of vendors, technical writers, and academic researchers who have a vast interest in maintaining the myth about the superior modelling of these technologies.
		Experienced analysts are not likely to accept modelling results without understanding why one decision is recommended over another and which assumptions are most critical.
		The accepted wisdom is that if models are based on principles that underlie the problem, and not fortuitous correlations, they are likely to perform well over time.
	www.reduct.com /About_Ai/buyers_guide.htm (934 words)

	Tech Report: HPL-2006-125: Predictive Modelling for Security
		We contend that investment decisions should be based on analytic models of the behaviour of information systems in the context of the environmental threats they face.
		We describe a mathematical framework, together with a modelling philosophy, for capturing the structural and dynamical properties of systems and their associated security operations.
		We show that our models are able to predict the economic consequences of investment decisions for security operations.
	www.hpl.hp.com /techreports/2006/HPL-2006-125.html?mtxs=rss-hpl-tr (183 words)

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