Search results for "Forecasting"
showing 10 items of 329 documents
The Berkeley Innovation Index: A Quantitative Approach to Measure, Track and Forecast Innovation Capability Within Individuals and Organizations
2018
Innovation and entrepreneurship are essential processes for human development, market growth, and technological breakthroughs, and it is vital for economic growth. Despite its importance, innovation is inherently difficult to measure and hence it is almost impossible for an individual or organization to know how they can improve their innovation output or claim that they are great at innovation. This paper presents a novel approach to measure and quantify innovation, called the Berkeley Innovation Index (BII). The BII characterizes and measures innovation capability of an individual or an organization. It builds on the hypothesis that innovation performance depends on the people, culture, a…
A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility.
2020
Land subsidence (LS) is a significant problem that can cause loss of life, damage property, and disrupt local economies. The Semnan Plain is an important part of Iran, where LS is a major problem for sustainable development and management. The plain represents the changes occurring in 40% of the country. We introduce a novel-ensemble intelligence approach (called ANN-bagging) that uses bagging as a meta- or ensemble-classifier of an artificial neural network (ANN) to predict LS spatially on the Semnan Plain in Semnan Province, Iran. The ensemble model's goodness-of-fit (to training data) and prediction accuracy (of the validation data) are compared to benchmarks set by ANN-bagging. A total …
Chromatographic retention–activity relationships for prediction of the toxicity pH-dependence of phenols
2007
Abstract An investigation of the use of the chromatographic retention (log k ) as an in vitro approach for modeling the pH-dependence of the toxicity to Guppy of phenols is developed. A data set of 19 phenols with available experimental toxicity–pH data was used. The importance of the mechanism of toxic action (MOA) of phenols was studied. log k data at three pH values were used for the phenols classification and two groups or ‘MODEs’ were identified. For one ‘MODE’ a quantitative retention–activity relationship (QRAR) model was calculated. Finally, the model was used to assess the toxicity to Guppy of phenols at different pH values. The results of this investigation suggest that chromato…
Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling
2017
Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed. The current study presents a series of individual and ensemble data mining methods including artificial neural network (ANN), support vector machine (SVM), maximum entropy (ME), ANN-SVM, ANN-ME, and SVM-ME to map gully erosion …
Non-parametric probabilistic forecasting of academic performance in Spanish high school using an epidemiological modelling approach
2013
Academic underachievement is a concern of paramount importance in Europe, and particularly in Spain, where around of 30% of the students in the last two courses in high school do not achieve the minimum knowledge academic requirement. In order to analyse this problem, we propose a mathematical model via a system of ordinary differential equations to study the dynamics of the academic performance in Spain. Our approach is based on the idea that both, good and bad study habits, are a mixture of personal decisions and influence of classmates. Moreover, in order to consider the uncertainty in the estimation of model parameters, a bootstrapping approach is employed. This technique permits to for…
Exponential smoothing with covariates applied to electricity demand forecast
2013
Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponen…
Infant mortality gap in the Baltic region - Latvia, Estonia, and Lithuania - in relation to macroeconomic factors in 1996-2010.
2013
Background and Objective. A constant gap has appeared in infant mortality among the 3 Baltic States - Latvia, Estonia, and Lithuania – since the restoration of independence in 1991. The aim of the study was to compare infant mortality rates in all the 3 Baltic countries and examine some of the macro- and socioeconomic factors associated with infant mortality. Material and Methods. The data were obtained from international databases, such as World Health Organization and EUROSTAT, and the national statistical databases of the Baltic States. The time series data sets (1996–2010) were used in the regression and correlation analysis. Results. In all the 3 Baltic States, a strong and significant…
Prospective de la relation formation-emploi dans un territoire : Richesse des outils, cohérence de l'analyse et incohérence dans l'action
2005
05111; Cette contribution porte sur la prospective en matière de relation formation-emploi tant au niveau régional qu'européen : où en sommes-nous de la capacité de mobilisation de l'information économique et sociale ? Jusqu'à quel point le partage de l'information entre acteurs régionaux est-il possible ? Quel est le rôle des informations dans l'aide à la décision ? Quel est le rapport de la connaissance à l'action ? La réflexion s'appuie sur une comparaison des démarches prospectives mises en oeuvre dans le secteur de l'hôtellerie-restauration dans certaines régions de trois pays européens : la France, la Tchéquie et la Slovénie. Elle souligne la richesse de l'outil statistique existant p…
Bayesian forecasting of demand time-series data with zero values
2013
This paper describes the development of a Bayesian procedure to analyse and forecast positive demand time-series data with a proportion of zero values and a high level of variability for the non-zero data. The resulting forecasts play decisive roles in organisational planning, budgeting, and performance monitoring. Exponential smoothing methods are widely used as forecasting techniques in industry and business. However, they can be unsuitable for the analysis of non-negative demand time-series data with the aforementioned features. In this paper, an unconstrained latent demand underlying the observed demand is introduced into the linear heteroscedastic model associated with the Holt-Winters…
Forecasting : theory and practice
2022
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a varie…