Lithium-Ion batteries require step-ahead information to apply contingency plans prevent them from operating beyond their safe operation thresholds in grid storage and electric vehicle applications. Recently, machine learning techniques have been increasingly applied forecast one such battery metric, State-of-Charge % ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://w...

This article considers the problem of order selection of the vector autoregressive moving-average models and of the sub-class of the vector autoregressive models under the assumption that the errors are uncorrelated but not necessarily independent. We propose a modified version of the AIC (Akaike information criterion). This criterion requires the estimation of the matrice involved in the asymp...

Identification of chemical reaction processes in subsurface environments is a key issue for reactive transport modeling because simulating different processes requires developing different chemical–mathematical models. In this paper, two sorption processes (equilibrium and kinetics) are considered for modeling neptunium and uranium sorption in fractured rock. Based on different conceptualizatio...

Premises and conclusions in classical syllogistic reasoning are formed using one of four quantifiers (All, Some, Some not, None). In everyday communication and reasoning, however, statements such as “most” and “few” are formed as well. So far only Chater and Oaksford’s (1999) Probability Heuristics Model (PHM) makes predictions for these so-called generalized quantifiers. In this article we (i)...

MARK T. HOLDER1,∗, PAUL O. LEWIS2, AND DAVID L. SWOFFORD3,4 1Department of Ecology and Evolutionary Biology, University of Kansas, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA; 2Department of Ecology and Evolutionary Biology, University of Connecticut, 75 North Eagleville Road, Unit 3043, Storrs, CT 06269-3043, USA; 3Institute for Genome Sciences and Policy Center for Evolutionary Genomics, D...

This note provides a proof of a fundamental assumption in the verification of bootstrap AIC variants in mixed models. The assumption links the bootstrap data and the original sample data via the log-likelihood function, and is the key condition used in the validation of the criterion penalty terms. (See Assumption 3 of both Shibata, 1997, and Shang and Cavanaugh, 2007.) To state the assumption,...

SUMMARY In order to measure the distance between a robust function evaluated under the true regression model and under a tted model, we propose a generalized Kullback-Leibler information. Using this generalization we have developed three robust model selection criteria, AICR , AICCR and AICCR, that allow the selection of candidate models that not only t the majority of the data, but also take i...

Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical informati...