Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art. [PDF]
Arch Comput Methods Eng, 2022 Bouaouda A, Sayouti Y.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Energy Strategy ReviewsThe synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling and forecasting tasks.
Eghbal Hosseini +7 more
doaj +1 more source
Rock mass classification prediction model using heuristic algorithms and support vector machines: a case study of Chambishi copper mine. [PDF]
Sci Rep, 2022 Hu J +5 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Comparison of heuristic approaches for the multiple depot vehicle scheduling problem
Given a set of timetabled tasks, the multi-depot vehicle scheduling problemis a well-known problem that consists of determining least-cost schedulesfor vehicles assigned to several depots such that each task is accomplishedexactly once by a vehicle.
Hertz, A. +3 more
core
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 +5 more
wiley +1 more source
Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter
Advanced Intelligent Discovery, EarlyView.We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon +3 more
wiley +1 more source
Minimizing makespan for mixed batch scheduling with identical machines and unequal ready times
Scientific ReportsThis study addresses the problem of minimizing the makespan for scheduling parallel batch machines, where jobs are processed in batches and each machine has the same capacity.
JinDian Huang
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