Results 51 to 60 of about 8,884,990 (247)

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani   +7 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns   +67 more
wiley   +1 more source

A new model for solving fuzzy linear fractional programming problem with ranking function [PDF]

open access: yesJournal of Applied Research on Industrial Engineering, 2017
In this paper, we studied fuzzy linear fractional programming (FLFP) problems with trapezoidal fuzzy numbers where the objective functions are fuzzy numbers and the constraints are real numbers.
Sapan Das, Tarni Mandal
doaj   +1 more source

Resolution of the linear fractional goal programming problem

open access: yesRect@, 2010
This work deals with the resolution of the goal programming problem with linear fraccional criteria. The main difficulty of these problems is the non-linear constraints of the mathematical programming models that have to be solved.
Hernández, Mónica, Caballero, Rafael
doaj  

استخدام خوارزمية طريقة تطوير مو لد قطع المستوي لإيجاد الحل العددي لمسائل البرمجة الكسرية [PDF]

open access: yesEngineering and Technology Journal, 2008
There are many methods for solving Fractional Programming problems thatgetting the optimal solution of the problem where the values of variables arefractional numbers not integer numbers, But when there are conditions in theproblem that requires the ...
doaj   +1 more source

A proposed method for solving multiobjective linear fractional programming problems with rough coefficients [PDF]

open access: yesDelta Journal of Science, 2016
In this paper, a new method for solving multiobjective linear fractional programming problems with roughcoefficient (MORLFP) is proposed. The MORLFP problem is considered by incorporating rough intervals in thecoefficients of the objective functions.
Mohamed Muamer, El-saeed Ammar
doaj   +1 more source

Strict Solution Method for Linear Programming Problem with Ellipsoidal Distributions under Fuzziness [PDF]

open access: yes, 2009
This paper considers a linear programming problem with ellipsoidal distributions including fuzziness. Since this problem is not well-defined due to randomness and fuzziness, it is hard to solve it directly.
Hasuike, Takashi, Katagiri, Hideki
core  

Enhancement of the Through‐Thickness Electrical Conductivity of Carbon‐Fiber‐Reinforced Plastics Using Large Graphite Particles

open access: yesAdvanced Engineering Materials, EarlyView.
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe   +6 more
wiley   +1 more source

Rotary 3D Printing With Integrated Electroplating

open access: yesAdvanced Engineering Materials, EarlyView.
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria   +5 more
wiley   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin   +14 more
wiley   +1 more source

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