Results 151 to 160 of about 2,735,316 (329)

Pareto or non-Pareto: Bi-criterion evolution in multi-objective optimization [PDF]

, 2015
It is known that Pareto dominance has its own weaknesses as the selection criterion in evolutionary multi-objective optimization. Algorithms based on Pareto dominance can suffer from slow convergence to the optimal front, inferior performance on problems
Yang, S, Li, Miqing; id_orcid, Liu, X, Li, M, Li, Miqing, Yang, Shengxiang, Liu, Xiaohui   +6 more
core   +1 more source

Physics‐Informed Machine Learning for Predicting Phases and Density of Al2O3–TiB2 Composites Synthesized via Laser Ignition From the Al–TiO2–B2O3–H3BO3 Reactive System

Advanced Intelligent Systems, EarlyView.
This interactive physics‐informed machine learning model predicts the composition and density of advanced ceramic materials produced by self‐propagating high‐temperature synthesis. The model requires user input processing parameters and demonstrates high accuracy.
Evangelos Daskalakis, Geeta Sharma, Sarathkumar Loganathan, Andrew Scott, Animesh Jha   +4 more
wiley   +1 more source

Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization [PDF]

Pareto set learning (PSL) is an emerging approach for acquiring the complete Pareto set of a multi-objective optimization problem. Existing methods primarily rely on the mapping of preference vectors in the objective space to Pareto optimal solutions in ...
Kou, Wei-Bin, Zhang, Jinyuan, Ye, Rongguang, Ishibuchi, Hisao, Chen, Longcan   +4 more
core   +1 more source

Rampant False Detection of Adaptive Phenotypic Optimization by ParTI-Based Pareto Front Inference. [PDF]

Mol Biol Evol, 2021
Sun M, Zhang J.
europepmc   +1 more source

Derivation of Pareto front with genetic algorithm and neural network

, 2020
It is common knowledge that the optimal values of the calibrated parameters of a rainfall-runoff model for one model response may not be the optimal values for another model response.
Chan, WT, Liong, SY, Khu, ST
core   +1 more source

Reverse Haptic Alerting: Human‐Centered Intelligent Systems That Turn Chemical and Biomedical Signals Into Felt Cues

Advanced Intelligent Systems, EarlyView.
Wearable sensors usually warn through sight or sound, channels that become unreliable under protective equipment or in noise. Reverse haptic alerting inverts this flow: Stimuli‐responsive materials convert chemical and biological signals into cues felt through the skin, while a machine‐learned digital twin of tactile perception personalizes the body ...
Hwanhee Yoo, Shin Hum Cho, Ku Kang, Yoon Jeong Jang, Chan‐Mo Yang, Doo‐Hee Lee   +5 more
wiley   +1 more source

EM-driven size reduction and multi-criterial optimization of broadband circularly-polarized antennas using pareto front traversing and design extrapolation. [PDF]

Sci Rep, 2022
Ullah U, Al-Hasan M, Koziel S, Mabrouk IB.   +3 more
europepmc   +1 more source

Automated Data‐Efficient Symbolic Regression for Interpretable Bioprocess Model Development

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Bioprocessing is central to the sustainable manufacture of pharmaceuticals, food products, and renewable chemicals. Consequently, developing high‐fidelity kinetic models to facilitate accurate process prediction, optimisation, and scale‐up is a top research priority.
Luca Riezzo, Alexander Rogers, Harry Kay, Dongda Zhang   +3 more
wiley   +1 more source

Accelerating green heterocyclic synthesis: Convergence of AI, automation, and sustainable chemistry

Bulletin of the Korean Chemical Society, EarlyView.
Green heterocyclic synthesis and data‐driven tools such as AI, high‐throughput experimentation, continuous flow, and self‐driving laboratories have developed largely in parallel. This review connects them and asks how green metrics such as E‐factor and PMI might serve as explicit optimization targets rather than post‐hoc measures, toward sustainable ...
Noor Aisyah Ahmad Shah, Amirreza Mottafegh, Su‐Hyun Yoo, Jongwoon Kim, Minseon Byeon, Juhwan Noh, Yea‐Lee Lee, Jin Suk Myung, Gwang‐Noh Ahn   +8 more
wiley   +1 more source

Integrating Recycling and Emission Reduction: A Business Strategy Analysis With Multi‐Objective Mixed‐Integer Linear Programming Framework for Optimising Sustainable Closed‐Loop Supply Chain Network Design

Business Strategy and the Environment, EarlyView.
ABSTRACT This research develops an integrated mixed‐integer linear programming (MILP) model for closed‐loop supply chain network design that optimises competing economic and environmental objectives including profit maximisation, supplier quality improvement and CO2 emission reduction.
Reza Eslamipoor
wiley   +1 more source