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PubMed1980

Daily hay fever forecast in the Netherlands. Radio broadcasting of the expected influence of the weather or subjective complaints of hay fever sufferers.

The literature on local pollen counts and their significance for hay fever is reviewed and a system for forecasting hay fever is described. Such forecasts have been broadcast by radio in The Netherlands since 1977. The hay fever forecast takes the form of a prognosis (in terms of three grades) of the influence of the expected whether situation on tomorrow's course of the subjective complaints of hay fever sufferers. It is not a forecast of the pollen count. When the subjective complaints of about 150 hay fever patients were used as reference for evaluation, the forecasts proved to have been correct in 72, 85, and 88% of the cases in 1977, 1978, and 1979, respectively. The practical usefulness and the limitations of the system are briefly discussed, with emphasis on the principle that not the local pollen count but the weather should be taken as the main determinative factor for the expected subjective experiences in a group of hay fever sufferers in a certain region.

Female↗

PubMed2007

On emotionally intelligent time travel: individual differences in affective forecasting ability.

In two studies, the authors examined whether people who are high in emotional intelligence (EI) make more accurate forecasts about their own affective responses to future events. All participants completed a performance measure of EI (the Mayer-Salovey-Caruso Emotional Intelligence Test) as well as a self-report measure of EI. Affective forecasting ability was assessed using a longitudinal design in which participants were asked to predict how they would feel and report their actual feelings following three events in three different domains: politics and academics (Study 1) and sports (Study 2). Across these events, individual differences in forecasting ability were predicted by participants' scores on the performance measure, but not the self-report measure, of EI; high-EI individuals exhibited greater affective forecasting accuracy. Emotion Management, a subcomponent of EI, emerged as the strongest predictor of forecasting ability.

Affect↗

PubMed2005

Developing a practical forecasting screener for domestic violence incidents.

In this article, the authors report on the development of a short screening tool that deputies in the Los Angeles Sheriff's Department could use in the field to help forecast domestic violence incidents in particular households. The data come from more than 500 households to which sheriff's deputies were dispatched in fall 2003. Information on potential predictors was collected at the scene. Outcomes were measured during a 3-month follow-up. Data were analyzed with modern data-mining procedures in which true forecasts were evaluated. A screening instrument was developed based on a small fraction of the information collected. Making the screening instrument more complicated did not improve forecasting skill. Taking the relative costs of false positives and false negatives into account, the instrument correctly forecasted future calls for service about 60% of the time. Future calls involving domestic violence misdemeanors and felonies were correctly forecast about 50% of the time. The 50% figure is important because such calls require a law enforcement response and yet are a relatively small fraction of all domestic violence calls for service.

Domestic Violence↗

PubMed2006

Forecasting influent flow rate and composition with occasional data for supervisory management system by time series model.

The information on the incoming load to wastewater treatment plants is not often available to apply modelling for evaluating the effect of control actions on a full-scale plant. In this paper, a time series model was developed to forecast flow rate, COD, NH4(+)-N and PO4(3-)-P in influent by using 250 days data of field plant operation data. The data for 150 days and 100 days were used for model development and model validation, respectively. The missing data were interpolated by the spline method and the time series model. Three different methods were proposed for model development: one model and one-step to seven-step ahead forecasting (Method 1); seven models and one-step-ahead forecasting (Method 2); and one model and one-step-ahead forecasting (Method 3). Method 3 featured only one-step-ahead forecasting that could avoid the accumulated error and give simple estimation of coefficients. Therefore, Method 3 was the reliable approach to developing the time series model for the purpose of this research.

Forecasting↗

PubMed2000

The clinical burden of prostate cancer in Canada: forecasts from the Montreal Prostate Cancer Model.

OBJECTIVES: The incidence of prostate cancer is increasing, as is the number of diagnostic and therapeutic interventions to manage this disease. We developed a Markov state-transition model--the Montreal Prostate Cancer Model--for improved forecasting of the health care requirements and outcomes associated with prostate cancer. We then validated the model by comparing its forecasted outcomes with published observations for various cohorts of men. METHODS: We combined aggregate data on the age-specific incidence of prostate cancer, the distribution of diagnosed tumours according to patient age, clinical stage and tumour grade, initial treatment, treatment complications, and progression rates to metastatic disease and death. Five treatments were considered: prostatectomy, radiation therapy, hormonal therapies, combination therapies and watchful waiting. The resulting model was used to calculate age-, stage-, grade- and treatment-specific clinical outcomes such as expected age at prostate cancer diagnosis and death, and metastasis-free, disease-specific and overall survival. RESULTS: We compared the model's forecasts with available cohort data from the Surveillance, Epidemiology and End Results (SEER) Program, based on over 59,000 cases of localized prostate cancer. Among the SEER cases, the 10-year disease-specific survival rates following prostatectomy for tumour grades 1, 2 and 3 were 98%, 91% and 76% respectively, as compared with the model's estimates of 96%, 92% and 84%. We also compared the model's forecasts with the grade-specific survival among patients from the Connecticut Tumor Registry (CTR). The 10-year disease-specific survival among the CTR cases for grades 1, 2 and 3 were 91%, 76% and 54%, as compared with the model's estimates of 91%, 73% and 37%. INTERPRETATION: The Montreal Prostate Cancer Model can be used to support health policy decision-making for the management of prostate cancer. The model can also be used to forecast clinical outcomes for individual men who have prostate cancer or are at risk of the disease.

Adult↗

PubMed2005

[Study on time-series analysis and forecast models on lung cancer incidence in Qidong, 1972 - 2001].

OBJECTIVE: To explore the lung cancer incidence rates from 1972 to 2001 and utilize varieties of models in forecasting trend up to 2010 in the city of Qidong, Jiangsu in order to provide baseline data for its control and prevention. METHODS: Using data from the cancer registry office in Qidong, we tried to reveal the trends of lung cancer incidence by analyzing the time-series on trends extrapolation, exponent smoothness, Box-Jenkins model etc. We also compared the prognostication precision, endow differ power, and established assembled forecast model. RESULTS: Data showed that there had been a rising trend of lung cancer from 1972 to 2001 and would still probably be on the increase in the future. The rate of male and female attained to 70 per 100 000 and 20 per 100 000, predicting that there would be a respective 33 percent and 10 percent increase in 2010. CONCLUSIONS: According to analysis of forecast models, it was right to prognosticate lung cancer incidence from time-series and improve forecast precision through developing combination models. The result of combination seemed close to ARIMA models which suggested that it could serve as a chief way to forecast the incidence of lung cancer.

China↗

PubMed1988

Status of menu item forecasting in dietetic education.

The status of forecasting techniques included in educational programs and the need for instructional material on this topic were investigated. A survey instrument was developed to determine which forecasting techniques were included in instructional programs. The validated questionnaire was mailed to directors of coordinated undergraduate programs or to Plan IV representatives at all universities with programs approved or accredited by the ADA. The response rate was 59%, or 156 dietetic programs. Analysis of the survey data revealed that mathematical techniques (Box-Jenkins, regression, exponential smoothing, moving average) were not taught in the majority of educational programs. Educators responded that forecasting was an important concept and that continuing education concerning forecasting techniques that may be employed in foodservice management was needed. As a result of the analysis of the data, two self-instructional modules that could be utilized by both practitioners and educators to enhance the level of practice and education were developed. Graduate and undergraduate students at 11 universities and 35 randomly selected practitioners tested the self-instructional modules. For all groups--undergraduate, graduate, and practitioners--the t-statistic was significant at the p less than .0000 level; thus the modules were effective in teaching foodservice forecasting concepts.

Dietary Services↗

PubMed1978

Menu item forecasting systems in hospital foodservice. A cost comparison of two- and three-echelon systems.

The forecasting efficiency of two- and three-echelon menu item forecasting systems was compared. Two forecasting models were used with each system, adaptive exponential smoothing and a Box-Jenkins model. The two systems were compared in terms of forecast error costs. The two-echelon system, using adaptive exponential smoothing, was recommended. This technique resulted in the lowest forecast error costs at a majority of the lead times which probably would be used most frequently. Also, this technique was the least complicated of the four techniques which were compared.

Computers↗

PubMed2000

Forecasts using neural network versus Box-Jenkins methodology for ambient air quality monitoring data.

This study explores ambient air quality forecasts using the conventional time-series approach and a neural network. Sulfur dioxide and ozone monitoring data collected from two background stations and an industrial station are used. Various learning methods and varied numbers of hidden layer processing units of the neural network model are tested. Results obtained from the time-series and neural network models are discussed and compared on the basis of their performance for 1-step-ahead and 24-step-ahead forecasts. Although both models perform well for 1-step-ahead prediction, some neural network results reveal a slightly better forecast without manually adjusting model parameters, according to the results. For a 24-step-ahead forecast, most neural network results are as good as or superior to those of the time-series model. With the advantages of self-learning, self-adaptation, and parallel processing, the neural network approach is a promising technique for developing an automated short-term ambient air quality forecast system.

Air Pollution, Indoor↗

PubMed2005

A dynamic model forecasting myocardial infarct size before, during, and after reperfusion therapy: an ASSENT-2 ECG/VCG substudy.

AIMS: Serial forecasts of final myocardial infarct (MI) size during fibrinolytic treatment (Rx) of ST-elevation MI would allow the identification of high-risk patients with a predicted major loss of viable myocardium, at a point when treatment may still be modified. We investigated a model for such forecasting, using time and the ECG. METHODS AND RESULTS: We collected 234 patients with ST-elevation MI, without signs of previous MI, bundle branch block, or hypertrophy. MI size was determined by the Selvester score and was "forecasted" at: admission with patients stratified by delay time and an ECG acuteness score into three groups (EARLY, DISCORDANT, and LATE); 90 min after Rx by > or =70% ST-recovery or not and occurrence of "reperfusion peaks"; 4 h after Rx by ST re-elevations. EARLY patients had smaller final infarct sizes than LATE (9.4 vs. 20%, P=0.01). EARLY patients with > or =70% ST-recovery without a reperfusion peak had smaller infarct sizes than those with (3.1 vs. 12.5%, P=0.001). EARLY patients without ST re-elevations had smaller infarct sizes (1.5%) than those with some (9%) or many re-elevations (12%), P<0.001. CONCLUSION: Final infarct size can be forecasted using delay time and serial ECGs. Serially updated forecasts seem especially important when both clock-time and initial ECG- signs indicate earliness.

Aged↗

PubMed1999

Improved Weather and Seasonal Climate Forecasts from Multimodel Superensemble.

A method for improving weather and climate forecast skill has been developed. It is called a superensemble, and it arose from a study of the statistical properties of a low-order spectral model. Multiple regression was used to determine coefficients from multimodel forecasts and observations. The coefficients were then used in the superensemble technique. The superensemble was shown to outperform all model forecasts for multiseasonal, medium-range weather and hurricane forecasts. In addition, the superensemble was shown to have higher skill than forecasts based solely on ensemble averaging.

Journal Article↗

PubMed2006

[Explanation and forecast: relapse of juvenile offenders].

On the basis of n=82 juvenile offenders from a prison for juvenile offenders in Rheinland Pfalz the model of the logistic regression is compared with a procedure from the family of the neural nets in its efficiency to explain and predict "relapse" in form of a renewed imprisonment or prosecution /police search after dismissal. The group which can be examined is limited by the population of the prison for juvenile offenders and the explaining variables for "relapse" as "addicted to drugs" present non-metric scaling. For the explanation only probabilities for "relapse" can be indicated in this connection. By means of this probability it is possible to classify the individual case. The forecast is simulated by coincidental dividing of the data: the first part of the data is used for the explanation, the second for the forecast. With the comparison of the logistic regression with the neural nets, the superiority of neural nets in the explanation of "relapse" can be shown, since the neural nets are able to consider dependence between the explaining variables and according to that they offer a differentiated explanation. Their efficiency to predict "relapse" depends on the comparability of the distribution in the two coincidentally provided samples, the training data record for determining the explanation and the test case for the use of the explanation regarding the forecast. For optimal explanation and forecast neural nets are to be preferred to the logistic regression, since in the model with the better explanation also includes the potential for a usable better forecast. Moreover the model of the logistic regression is in fact a special case of the neural net, with a reduced complexity of the net.

Adolescent↗

PubMed1992

Modeling and forecasting U.S. sex differentials in mortality.

"This paper examines differentials in observed and forecasted sex-specific life expectancies and longevity in the United States from 1900 to 2065. Mortality models are developed and used to generate long-run forecasts, with confidence intervals that extend recent work by Lee and Carter (1992). These results are compared for forecast accuracy with univariate naive forecasts of life expectancies and those prepared by the Actuary of the Social Security Administration."

Americas↗

PubMed1983

Small area population forecasting: some experience with British models.

This study is concerned with the evaluation of the various models including time-series forecasts, extrapolation, and projection procedures, that have been developed to prepare population forecasts for planning purposes. These models are evaluated using data for the Netherlands. "As part of a research project at the Erasmus University, space-time population data has been assembled in a geographically consistent way for the period 1950-1979. These population time series are of sufficient length for the first 20 years to be used to build models and then evaluate the performance of the model for the next 10 years. Some 154 different forecasting models for 832 municipalities have been evaluated. It would appear that the best forecasts are likely to be provided by either a Holt-Winters model, or a ratio-correction model, or a low order exponential-smoothing model."

Demography↗

PubMed1994

Small area demographic forecasts.

The author reviews the literature on small area forecasting with a focus on the work of Robert Schmitt. He finds that "the accuracy of small area forecasts has not increased appreciably over the past four decades, despite methodological progress, increased knowledge gained from the evaluation of forecasts, and more widely available and rich data. A comment made by Schmitt 40 years ago is still largely true today, 'No method is yet known for forecasting the population of small urban areas with a high degree of accuracy'...."

Demography↗

PubMed1992

Uncertainty variants of population forecasts.

"When using population forecasts it is important to take into account the degree of uncertainty of the results. For that reason the Netherlands Central Bureau of Statistics publishes low and high variants next to the most probable medium variant.... The width of the interval between the variants is based on an analysis of previous forecast errors. The degree of uncertainty of the various forecast results turns out to vary strongly.... On the basis of a statistical time-series model of forecast errors of total population growth, a confidence interval of total population size can be estimated."

Demography↗

PubMed1995

[Demography perspectives and forecasts of the demand for electricity].

"Demographic perspectives form an integral part in the development of electric load forecasts. These forecasts in turn are used to justify the addition and repair of generating facilities that will supply power in the coming decades. The goal of this article is to present how demographic perspectives are incorporated into the electric load forecasting in Quebec. The first part presents the methods, hypotheses and results of population and household projections used by Hydro-Quebec in updating its latest development plan. The second section demonstrates applications of such demographic projections for forecasting the electric load, with a focus on the residential sector." (SUMMARY IN ENG AND SPA)

Americas↗

PubMed1998

Tools for immunization guideline knowledge maintenance. I. Automated generation of the logic "kernel" for immunization forecasting.

IMM/Def is a prototype computer program designed to facilitate the building and maintenance of a rule-based program which performs childhood immunization forecasting. An immunization forecasting program takes as input a child's immunization history and produces recommendations as to which vaccinations are due and which should be scheduled next. A significant amount of the knowledge required for immunization forecasting can be expressed in tabular form, including the parameters that indicate the minimum age when each dose may be given and the minimum intervals between doses. The choice of which of these sets of parameters apply to a particular case depends upon additional clinical logic. To perform forecasting, this logic must be applied in three temporal contexts: (1) a dose is due now, (2) a dose is not yet due, and (3) a dose must be scheduled to follow a dose which is due now. Building and maintaining this logic by hand is a formidable challenge. IMM/Def demonstrates how this task can be simplified by first defining immunization "definition logic" which can be automatically translated into if-then rules for each of the three contexts. The approach has been applied successfully to the six childhood vaccination series which are routinely administered. A key advantage is that IMM/Def allows one to have two specifications of the logic that can be examined independently and that can be cross-checked to help assure completeness, consistency, and accuracy of the logic. The paper describes how IMM/Def performs its translation and discusses several design issues and lessons learned.

Child↗