Results 91 to 100 of about 66,012 (265)
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Context Awareness and Human–Robot Interaction Optimization for Museum Intelligent Guide Robot
Advanced Intelligent Systems, EarlyView.This study presents a context‐aware human–robot interaction framework designed for intelligent museum guide robots. The system features a three‐layer architecture—perception, understanding, and behavior execution—that enables adaptive and meaningful interactions with museum visitors.
Anna Zou, Yue Meng, Shijing Tong
wiley +1 more source
Learning the Pareto Front with Hypernetworks
, 2020 Accepted to ICLR ...
Navon, Aviv +3 more
openaire +2 more sources
Advanced Intelligent Systems, EarlyView.This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
PLoS ONEBi-objective optimization problems arise when a process needs to be optimized with respect to two conflicting objectives. Solving such problems produces a set of points called the Pareto front, where no objective can be improved without worsening at ...
Ihab Hashem +3 more
doaj +1 more source
ND-Tree-based update: a Fast Algorithm for the Dynamic Non-Dominance Problem
, 2017 In this paper we propose a new method called ND-Tree-based update (or shortly ND-Tree) for the dynamic non-dominance problem, i.e. the problem of online update of a Pareto archive composed of mutually non-dominated points.
Jaszkiewicz, Andrzej, Lust, Thibaut
core +2 more sources
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Advances in Mechanical Engineering, 2016 Real-time traffic control is very important for urban transportation systems. Due to conflicts among different optimization objectives, the existing multi-objective models often convert into single-objective problems through weighted sum method.
Pengpeng Jiao, Ruimin Li, Zhihong Li
doaj +1 more source
A multi-objective genetic algorithm for the design of pressure swing adsorption [PDF]
, 2009 Pressure Swing Adsorption (PSA) is a cyclic separation process, more advantageous over other separation options for middle scale processes. Automated tools for the design of PSA processes would be beneficial for the development of the technology, but ...
Brandani, S., Fiandaca, G., Fraga, E.S.
core
Optimal Signaling of MISO Full-Duplex Two-Way Wireless Channel
, 2015 We model the self-interference in a multiple input single output (MISO) full-duplex two-way channel and evaluate the achievable rate region. We formulate the boundary of the achievable rate region termed as the Pareto boundary by a family of coupled, non-
Aazhang, Behnaam, Jia, Shuqiao
core +1 more source