Results 121 to 130 of about 3,045 (214)

Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou, Juan Zou, Gan Ruan, Yuan Liu, Yizhang Xia   +4 more
wiley   +1 more source

Evolutionary Dynamic Multiobjective Optimisation Assisted by Inverse Regression Tree Predictor

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Dynamic multiobjective optimisation problems (DMOPs) are optimisation problems with multiple conflicting objectives that can change over time. Most dynamic multiobjective optimisation evolutionary algorithms (DMOEAs) attempt to estimate Pareto‐optimal sets (PS) directly in the decision space.
Kai Gao, Lihong Xu
wiley   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

Not all Temperature Shocks are Alike: Disentangling Heat and High Temperature Shocks and Their Effects on Inflation in Australia

Economic Record, EarlyView.
We study the effects of heat and high temperature shocks on inflation in Australia using monthly, state‐level temperature anomaly data via two stages. In the first stage, we decompose temperature anomalies into orthogonal components using a structural vector autoregression with long‐run restrictions.
Tan Dat Huynh, Mengheng Li
wiley   +1 more source

Statistical analyses of ecological multinomial time series to identify environmental drivers and biotic interactions

Methods in Ecology and Evolution, EarlyView.
Abstract Understanding the drivers of change in communities is a major goal of paleoecology and community ecology, but statistical inference from multivariate time series is challenged by relative (rather than absolute) abundance data, observation uncertainty and missing data due to uneven sampling through time.
Quinn Asena, John W. Williams, Jonathan Johnson, Bryan Shuman, Vania Stefanova, Anthony Ives   +5 more
wiley   +1 more source

Extending reliability to intensive longitudinal data with the Kalman filter

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Reliability is central to how researchers approach measurement in standard, group‐based analyses of single‐time‐point data, yet this critical aspect is often overlooked in the analysis of repeated observations. Since its inception, reliability has been a between‐person concept, but we redevelop this notion for within‐person designs by ...
Michael D. Hunter
wiley   +1 more source

Development and analytical validation of a targeted short‐read next generation sequencing‐based pharmacogenetic panel for comprehensive variant detection

British Journal of Pharmacology, EarlyView.
Abstract Background and Purpose Genomic profiling of patients for genetic variants that modify the effect of specific medications has many benefits, including the possibility of avoiding toxicities and ensuring an adequate effect of the medication. Our intention was to develop a comprehensive, high‐quality pharmacogenetic test panel for clinical use ...
Anna Gréen, Nils Johan Fredriksson, Michael Andresen, Jon Jonasson, Malin Lindqvist Appell, Henrik Gréen   +5 more
wiley   +1 more source

L‐VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

Computer Graphics Forum, EarlyView.
L‐VISP is a human‐machine solution that uses visual analytics for LSTM modelling in clinical research. L‐VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context.
C. Floricel, Y. Wang, A. Wentzel, C. D. Fuller, G. E. Marai, M. E. Papka, G. Canahuate   +6 more
wiley   +1 more source

Macroeconomic forecasting during recessions and expansions in the US and the euro area

Economic Inquiry, EarlyView.
Abstract This study systematically evaluates forecasting performance of 11 Dynamic Stochastic General Equilibrium (DSGE) and 2 Bayesian Vector Autoregression (BVAR) models during recessions and expansions in the US and the euro area. Results show that no single model dominates: parsimonious models perform well in stable periods and at short horizons ...
Jan Čapek, Jakub Chalmovianský, Vlastimil Reichel   +2 more
wiley   +1 more source

Site Fidelity, Depth Preference and Vertical Movement Patterns of Lentic and Lotic European Catfish Silurus glanis

Fisheries Management and Ecology, EarlyView.
ABSTRACT To study variables that may trigger the dispersion of the currently expanding European catfish in its native distribution limits, 42 individuals were captured from Upper Lake Constance (lentic) and 42 from two streaming tributaries (lotic), fitted with pressure and temperature loggers, and released at the site of capture (control: lotic or ...
Albert Ros, Jan Baer, Matthias Fromherz, Juergen Geist, Alexander Brinker   +4 more
wiley   +1 more source