Results 91 to 100 of about 1,432,311 (298)

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, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Vilfredo Pareto. Manuale di Economia Politica. Edizione critica

, 2006
Il volume è l'edizione critica del "Manuale di economia politica" di V. Pareto. Oltre la ripubblicazione del Manuale, insieme con le aggiunte introdotte da Pareto nella traduzione francese, vi è un ampio corredo di note che inquadrano la trattazione ...
Zanni, A, Bruni, L., VILFREDO PARETO, Montesano, ALDO MARIA   +3 more
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Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization.

PLoS ONE
Bi-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, Viviane De Buck, Seppe Seghers, Jan Van Impe   +3 more
doaj   +1 more source

Out in Front Program Application Form for 2015-2016

, 2015
Copy of the online application form to apply to the Out in Front leadership ...
Out in Front
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Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan, Min Jiang, Wentao Huang, Qingchao Jiang   +3 more
wiley   +1 more source

Deep Q-Managed: a new framework for multi-objective deep reinforcement learning

Frontiers in Artificial Intelligence
This paper introduces Deep Q-Managed, a novel multi-objective reinforcement leaning (MORL) algorithm designed to discover all policies within the Pareto Front.
Richardson Menezes, Richardson Menezes, Thiago Henrique Freire de Oliveira, Luiz Paulo de Souza Medeiros, Adrião Duarte Dória Neto   +4 more
doaj   +1 more source

On the Pareto Type III distribution [PDF]

This short note analyzes the distributional properties of Pareto Type III random variables. We introduce a three parameters version of the orignal two parameters distribution proposed by Pareto and derive both the density and the characteristic function.
Giulio Bottazzi
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