Results 131 to 140 of about 34,160 (311)
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker +3 more
wiley +1 more source
Review on Automated Storage and Retrieval System for Warehouse
The swift expansion of e-commerce and supply chain operations has significantly enhanced the efficiency of warehouse management systems, establishing them as vital components in augmenting organizations' competitiveness. This paper delves into warehouse
Alex Low Kai Jie +2 more
doaj +1 more source
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc +8 more
wiley +1 more source
A Grouping Genetic Algorithm for the Order Batching Problem in Distribution Warehouses [PDF]
Order picking is a warehouse function that deals with the retrieval of articles from their storage locations in order to satisfy certain customer demands. Combining several single customer orders into one (more substantial) picking order can increase the
Sören Koch, Gerhard Wäscher
core
We discovered novel materials with giant dielectric constants by combining first‐principles phonon calculations and machine learning. Screening 525 perovskites identified six candidates. RbNbO3 was synthesized under pressure and showed ε ≈ 800–1000. This validates our framework as a powerful tool for high‐performance dielectric materials discovery.
Hiroki Moriwake +9 more
wiley +1 more source
DESIGN OF PICKER-TO-PARTS WAREHOUSE FULFILLMENT SECTIONS USING SURROGATE MACHINE LEARNING MODEL
The design of picker-to-parts warehouse sections contains various decision parameters such as warehouse dimensions, routing policy, and storage assignment policy.
Basava Sri Krishna Vamsy, Lanka
core
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
A focus of many business curricula is on information management including special topics such as Data Warehousing. In real life system architects usually encounter the question of ?how to design a Data Warehouse?
Hecht, Sonja;Schmidl, Jörg;Weckenmann, Daniela;Wittges, Holger;Krcmar, Helmut
core

