A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure by Chenfeng Li, Tenglong Jin, Zequan Chen, Guanchen Wei

“…Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. …”
Get full text

VARIATION OF EMBRYO WEIGHT IN BREEDING ACCESSIONS OF CARROT by A. F. Bukharov, D. N. Baleev, M. I. Ivanova

“…The method of maximum likelihood was used to  reveal correspondences  of  experimental function  of distribution in embryo weight in seed population of accessions studied  and  normal  distribution.  …”
Get full text

Thermoelastic damping in piezothermoelastic nanobeam resonators under the strain gradient theory with micro-inertia and non-fourier heat conduction by Olha Hrytsyna, Maryan Hrytsyna

“…To account for small-scale effects, the Helmholtz free energy density is defined as a function of the strain tensor, strain gradient tensor, electric field vector, and temperature field, considering these parameters as independent state variables. …”
Get full text

High-accuracy solution of pantograph differential equations subject to mixed boundary conditions via shifted Vieta–Lucas polynomials by R. M. Hafez, H. M. Ahmed

“…A Galerkin method (GM) is formulated for constant coefficient-type equations, and a spectral collocation method (SCM) is given for variable coefficient cases. …”
Get full text

Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer by Ashley M Henneghan, Emily W Paolillo, Kathleen M Van Dyk, Oscar Y Franco-Rocha, Soyeong Bang, Rebecca Tasker, Tara Kaufmann, Darren Haywood, Nicolas H Hart, Raeanne C Moore

“…Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. …”
Get full text

Flexible Reconfiguration for Optimal Operation of Distribution Network Under Renewable Generation and Load Uncertainty by Behzad Esmaeilnezhad, Hossein Amini, Reza Noroozian, Saeid Jalilzadeh

“…Minimizing the operational costs is difficult when there is a high penetration of renewable resources and variability of loads, which introduces uncertainty. …”
Get full text

Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
Get full text

A robust optimization model for allocation-routing problems under uncertain conditions. by Tingting Zhang, Yanqiu Liu

“…Temporary hospital capacity significantly influences the objective function more than general hospitals. As the problem size increases, the robust optimization model performs better than the deterministic model. …”
Get full text

DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…This paper proposes a novel hybrid technique, termed Decision Tree with Hill Climbing (DTHC), for efficient spectrum hole detection in CRNs. The objective of the DTHC method is to improve detection accuracy while minimizing false alarm rates. …”
Get full text

IrrigApp: An Online Tool for Determining Crop Water Use and Evaluating Irrigation Scheduling Options by José O. Payero

“…., county, crop, soil type, start date, end date, irrigation applications, and irrigation efficiency). IrrigApp calculates daily crop evapotranspiration (ETc) and conducts a daily soil water balance to estimate several daily and seasonal variables, such as ETc under dryland and irrigated conditions, soil water content in the crop root zone, and water losses by runoff and deep percolation. …”
Get full text

Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…The sum of the frequency-weighted RMS of the driver seat acceleration, the RMS of dynamic tyre load, and suspension working space is taken as the objective function in this article, using nonlinear damping coefficients and stiffness of suspension as design variables. …”
Get full text

Optimum System Design Using Rough Interval Multi-Objective De Novo Programming by Iftikhar Hussein, Hegazy Zaher, Naglaa Ragaa Saeid, Hebaa Sayed Roshdy

“…This paper suggested a new approach for solving uncertainty of De novo programming problems (DNP) using a combination model consisting of a rough interval multi-objective programming (RIMOP) and DNP, where coefficients of decision variables of objective functions and constraints are rough intervals (RIC). …”
Get full text

Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms by Nicolás Faedo, Giordano Scarciotti, Alessandro Astolfi, John V. Ringwood

“…The authors develop a framework under which the objective function (and system variables) can be mapped to a finite‐dimensional tractable quadratic program (QP), which can be efficiently solved using state‐of‐the‐art solvers. …”
Get full text

Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…A five-dimensional objective system—comprising energy efficiency, spatial quality, economic cost, ecological benefits, and cultural expression—was established, alongside the identification and standardization of 29 key variables to construct mapping relationships among objective functions. …”
Get full text

Semantic ECG hash similarity graph by Yixian Fang, Shilin Zhang, Yuwei Ren

“…Subsequently, a lightweight linear hash function is utilized to produce a hash representation for the unseen signal. …”
Get full text

Structural strength analysis and optimization of converter lug based on Kriging model by HE Guanqiang, LIU Yongjiang, LI Hua, CHEN Liming

“…In this paper, machine learning methods were considered to approximate the functional relationships between design variables and responses. …”
Get full text

An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. The minimum manufacturing cost of ship hull shell plates (SHSPs) is the objective function, the rules and requirements for the seam position and the size of a single shell plate are the constraints, and the position and shape of the seam are the design variables. …”
Get full text

Neuro-Evolution of Augmenting Topologies for Dynamic Scheduling of Flexible Job Shop Problem by Jian Huang, Yarong Chen, Jabir Mumtaz, Liuyan Zhong

“…This study introduces a neuro-evolution of augmenting topologies (NEAT) algorithm aimed at optimizing the scheduling efficiency in flexible job shops by minimizing both maximum completion and average lag times, taking into account variables like sporadic job arrivals, variable machining durations, tool wear, preventive maintenance, and equipment failures. …”
Get full text

Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
Get full text

Ionospheric Correction Based on Ingestion of Global Ionospheric Maps into the NeQuick 2 Model by Xiao Yu, Chengli She, Weimin Zhen, Nava Bruno, Dun Liu, Xinan Yue, Ming Ou, Jisheng Xu

“…The accuracy of TEC prediction can be improved further through performing a four-coefficient function expression of Az versus MODIP. …”
Get full text