Results 111 to 120 of about 2,735,316 (329)
Multi-Objective Feature Selection Method Based on Hybrid MI and PSO Algorithm
Jisuanji kexue yu tansuo, 2020 Feature selection is an important pre-processing in data mining, due to a lot of redundant and irrelevant features in datasets. A filter-wrapper multi-objective feature selection method based on hybrid mutual information and particle swarm optimization ...
WANG Jinjie, LI Wei
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Pareto front feature selection based on artificial bee colony optimization
Information Sciences, 2018 © 2017 Elsevier Inc. Feature selection has two major conflicting aims, i.e., to maximize the classification performance and to minimize the number of selected features to overcome the curse of dimensionality. To balance their trade-off, feature selection
Emrah Hançer +4 more
semanticscholar +1 more source
Device Stochasticity Directly Implements Bayesian Sampling in Spiking Neurons
Advanced Science, EarlyView.Brain‐inspired stochastic spiking turns device noise into Bayesian uncertainty for robust, low‐power neuromorphic computing. ABSTRACT Device stochasticity is considered a non‐ideality in neuromorphic hardware, although stochastic neural activity supports probabilistic computation in biological systems.
Huannan Zheng, Jingli Liu, Kezhou Yang
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AMB ExpressT and B cell activation are equally important in triggering and orchestrating adaptive host responses to design multi-epitope African swine fever virus (ASFV) vaccines.
Ting-Yu Chen +5 more
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Pareto Front Analysis of a Multiobjective MPC-Based EMS for a Series Hybrid Electric Tractor
IEEE AccessThis paper presents a multi-objective model predictive control-based energy management system. The proposed scheme design aims to perform the power sharing among available sources, minimizing the diesel engine fuel consumption, and regulating the battery
Gonzalo Curiel-Olivares +4 more
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Spectral-Energy Efficiency Pareto Front in Cellular Networks: A Stochastic Geometry Framework
IEEE Wireless Communications Letters, 2019 We compute the spectral-energy efficiency Pareto front in Poisson cellular networks, by formulating a spectral-energy efficiency bi-objective optimization problem as a function of either the transmit power or the density of the base stations ...
M. di Renzo +3 more
semanticscholar +1 more source
Multiobjective Test Problems with Degenerate Pareto Fronts
CoRR, 2018 In multiobjective optimisation, a set of scalable test problems with a variety of features allow researchers to investigate and evaluate the abilities of different optimisation algorithms, and thus can help them to design and develop more effective and efficient approaches.
Liangli Zhen +4 more
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Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Advanced Electronic Materials, EarlyView.Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
Modelling and Simulation in Engineering, 2017 Most of the modern multiobjective optimization algorithms are based on the search technique of genetic algorithms; however the search techniques of other recently developed metaheuristics are emerging topics among researchers. This paper proposes a novel
Vimal Savsani +3 more
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Redundancy and delimitation of the Pareto front
Operational ResearchAbstract The purpose of this paper is to investigate the constraints shaping the Pareto front in multi-objective linear programming, by applying recently proposed single-objective optimization methods to individual linear programming problems, constructed from the given problem.
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