Results 91 to 100 of about 3,693 (219)
A cooperative hyper-heuristic search framework [PDF]
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Ouelhadj, Djamila, Petrovic, S.
openaire +3 more sources
Sub‐optimal Internet of Thing devices deployment using branch and bound method
The main contributions of this paper are (1) IoT network deployment problem formation as MILP problem to optimise the transmission among network nodes, and (2) New BB method with a machine learning function to reduce the computational complexity. Abstract The Internet of Thing (IoT) network deployments are widely investigated in 4G and 5G systems and ...
Haesik Kim
wiley +1 more source
This paper introduces a novel neuromorphic-inspired hyper-heuristic framework (NeuHH) for solving the Capacitated Single-Allocation p-Hub Location Routing Problem (CSAp-HLRP), a challenging combinatorial optimization problem that jointly addresses hub ...
Kassem Danach +3 more
doaj +1 more source
Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool [PDF]
In this paper we present a new version of a GP financial forecasting tool, called EDDIE 8. The novelty of this version is that it allows the GP to search in the space of indicators, instead of using pre-specified ones.
Austin M. +18 more
core +3 more sources
Abstract In this paper, we present a foray into the computational study of anthropological texts. Drawing on a corpus of approximately 2,500 articles published in the Journal of the Royal Anthropological Institute (formerly Man) from 1950 to 2018, we discuss selected findings from the deployment of two methods for computational text analysis, namely ...
Kristoffer Albris +4 more
wiley +1 more source
Abstract In this article we apply Wacquant's conceptualization of the ghetto to an analysis of interviews conducted with Roma people living in the state‐enforced camps of Turin, Italy. We illustrate how the elements characterizing a ghetto according to Wacquant (i.e.
Vincenzo Romania, Tommaso Bertazzo
wiley +1 more source
Hierarchical Differentiable Fluid Simulation
We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong +4 more
wiley +1 more source
Hyper-Heuristics and Scheduling Problems: Strategies, Application Areas, and Performance Metrics
Scheduling problems, which involve allocating resources to tasks over specified time periods to optimize objectives, are crucial in various fields. This work presents hyper-heuristic applications for scheduling problems, analyzing 215 peer-reviewed ...
Alonso Vela +4 more
doaj +1 more source
Working with OpenCL to Speed Up a Genetic Programming Financial Forecasting Algorithm: Initial Results [PDF]
The genetic programming tool EDDIE has been shown to be a successful financial forecasting tool, however it has suffered from an increase in execution time as new features have been added. Speed is an important aspect in financial problems, especially in
Backus J. +3 more
core +1 more source
Adaptive Sampling for BRDF Acquisition
We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi +3 more
wiley +1 more source

