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This paper presents a genetic-based hybrid algorithm that combines the exploration power of Genetic Algorithm (GA) with the exploitation capacity of a phenotypical probabilistic local search algorithm. Though not limited to a certain class…

Optimization and Control · Mathematics 2016-11-26 Reza Najian Asl , Mohamad Aslani , Masoud Shariat Panahi

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective…

Machine Learning · Computer Science 2023-01-24 William Marfo , Deepak K. Tosh , Shirley V. Moore

In this paper, we propose a novel online optimization algorithm built by combining ideas from control theory and system identification. The foundation of our algorithm is a control-based design that makes use of the internal model of the…

Optimization and Control · Mathematics 2025-11-26 Wouter J. A. van Weerelt , Lantian Zhang , Silun Zhang , Nicola Bastianello

We propose a new algorithm for the solution of the robust multiple-load topology optimization problem. The algorithm can be applied to any type of problem, e.g., truss topology, variable thickness sheet or free material optimization. We…

Optimization and Control · Mathematics 2013-07-30 Michal Kocvara

Most reported research for monitoring health of pipelines using ultrasonic guided waves (GW) typically utilize bulky piezoelectric transducer rings and laboratory-grade ultrasonic non-destructive testing (NDT) equipment. Consequently, the…

Signal Processing · Electrical Eng. & Systems 2024-03-19 Sheetal Patil , Sauvik Banerjee , Siddharth Tallur

This paper proposes a thresholding approach for crack detection in an unmanned aerial vehicle (UAV) based infrastructure inspection system. The proposed algorithm performs recursively on the intensity histogram of UAV-taken images to…

Computer Vision and Pattern Recognition · Computer Science 2018-12-20 Q. Zhu , T. H. Dinh , V. T. Hoang , M. D. Phung , Q. P. Ha

We present FIRE, Fast Interpretable Rule Extraction, an optimization-based framework to extract a small but useful collection of decision rules from tree ensembles. FIRE selects sparse representative subsets of rules from tree ensembles,…

Machine Learning · Computer Science 2023-06-14 Brian Liu , Rahul Mazumder

Structural learning, a method to estimate the parameters for discrete energy minimization, has been proven to be effective in solving computer vision problems, especially in 3D scene parsing. As the complexity of the models increases,…

Computer Vision and Pattern Recognition · Computer Science 2017-01-13 Mengtian Li , Daniel Huber

The robust truss topology optimization against the uncertain static external load can be formulated as mixed-integer semidefinite programming. Although a global optimal solution can be computed with a branch-and-bound method, it is very…

Optimization and Control · Mathematics 2019-01-25 Yoshihiro Kanno

Unmanned Aerial Vehicles (UAVs) are transforming infrastructure inspections in the Architecture, Engineering, Construction, and Facility Management (AEC+FM) domain. By synthesizing insights from over 150 studies, this review paper…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Amir Farzin Nikkhah , Dong Chen , Bradford Campbell , Somayeh Asadi , Arsalan Heydarian

Real-world systems are often complex, dynamic, and nonlinear. Understanding the dynamics of a system from its observed time series is key to the prediction and control of the system's behavior. While most existing techniques tacitly assume…

Computation · Statistics 2015-05-19 Bing Wang , Jie Sun , Adilson E. Motter

This study investigates the combined use of generative grammar rules and Monte Carlo Tree Search (MCTS) for optimizing truss structures. Our approach accommodates intermediate construction stages characteristic of progressive construction…

Computational Engineering, Finance, and Science · Computer Science 2025-04-03 Gabriel Garayalde , Luca Rosafalco , Matteo Torzoni , Alberto Corigliano

In this paper, we adopt a probability distribution estimation perspective to explore the optimization mechanisms of supervised classification using deep neural networks. We demonstrate that, when employing the Fenchel-Young loss, despite…

Machine Learning · Computer Science 2025-04-01 Binchuan Qi , Wei Gong , Li Li

There are many different nature-inspired algorithms in the literature, and almost all such algorithms have algorithm-dependent parameters that need to be tuned. The proper setting and parameter tuning should be carried out to maximize the…

Computation · Statistics 2025-04-29 Geethu Joy , Christian Huyck , Xin-She Yang

This study presents a methodology to treat performance-based seismic design as an inverse engineering problem, where design parameters are directly derived to achieve specific performance objectives. By implementing explainable machine…

Machine Learning · Computer Science 2025-08-04 Mohsen Zaker Esteghamati

Modern computers enable methods for design optimization that account for uncertainty in the system---so-called optimization under uncertainty. We propose a metric for OUU that measures the distance between a designer-specified probability…

Optimization and Control · Mathematics 2015-08-10 Pranay Seshadri , Paul Constantine , Gianluca Iaccarino , Geoffrey Parks

A SHM method is proposed that minimises the required number of sensors for detecting damage. The damage detection method consists of two steps. In an initial characterization step, substructuring approach is applied to the healthy structure…

Systems and Control · Computer Science 2016-02-02 Unai Ugalde , Javier Anduaga , Fernando Martinez , Aitzol Iturrospe

We analyze damage propagation modeling of turbo-engines in a data-driven approach. We investigate subspace tracking assuming a low dimensional manifold structure and a static behavior during the healthy state of the machines. Our damage…

Signal Processing · Electrical Eng. & Systems 2019-07-29 Farhan Khan

There is high demand on fire simulations, in both scale and quantity. We present a multi-pronged approach to improving the time and energy required to meet these demands. We show the ability of a custom machine learning surrogate model to…

Machine Learning · Computer Science 2025-10-01 James Panayis , Matt Field , Vignesh Gopakumar , Andrew Lahiff , Kristian Zarebski , Aby Abraham , Jonathan L. Hodges

This paper presents tractable reformulations of topology optimization problems of structures subject to frictionless unilateral contact conditions. Specifically, we consider stiffness maximization problems of trusses and continua. Based on…

Optimization and Control · Mathematics 2020-11-17 Yoshihiro Kanno
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