10 June 2020
The identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data (IHACRES) model has been proven to be an efficient yet basic model to simulate rainfall–runoff processes due to the difficulty in o...
The relationship between the host and the microbiome, or the assemblage of microorganisms (including bacteria, archaea, fungi, and viruses), has been proven crucial for its health and disease development. The high dimensionality of microbiome dataset...
This paper uses a nature-inspired optimization algorithm to discuss the automatic selection of control structure parameters. The commonly used quality indicators are presented and analyzed for the optimization process of the control system. Moreover,...
Feature selection is becoming a relevant problem within the field of machine learning. The feature selection problem focuses on the selection of the small, necessary, and sufficient subset of features that represent the general set of features, elimi...
This study developed a robust parameter set (ROPS) selection framework for a rainfall-runoff model that considers multi-events using the Pareto optimum and minimax regret approach (MRA). The calibrated parameter sets based on the Nash-Sutcliffe coeff...
Traditional convolutional neural networks face challenges in handling multi-scale targets in remote sensing object detection due to fixed receptive fields and simple feature fusion strategies, which affect detection accuracy. This study proposes an a...
In recent years, the share of renewable energy in the distribution network has been increasing. To deal with high renewable energy penetration, it is important to improve the energy efficiency and stability of the distribution network. In this paper,...
It is still largely unknown to what extent domestication, ancestry, or recent functional selection are responsible for the behavioral differences in whether dogs look back to a human when presented with a difficult task. Here, we tested whether this...
The problem of optimizing a causal objective function emerged in recent work, where the behavior of objects needs to be expressed in terms of interventional or counterfactual probabilities. A key example is the unit selection problem introduced by Li...
In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based imag...
This paper explores the energy-intensive cement industry, focusing on a plant in Greece and its mill and kiln unit. The data utilized include manipulated, non-manipulated, and uncontrolled variables. The non-manipulated variables are computed based o...
Background/Objectives: Adaptive functioning involves the integration of bodily states with emotional information from the external environment. Interoceptive functioning and spatial cognition may contribute to this integration, but their joint associ...
This paper investigates the effect of selected strategies of distributed energy resources (DER) on an energy cost function that optimizes the distribution of distributed energy resources for a mid-rise apartment building. This is achieved through com...
The diversity and non-uniformity of the positioning systems available in maritime navigation systems often impede the watchkeeping officer in the selection of the appropriate positioning system, in particular, in restricted basins. Thus, it is necess...
In high-dimensional space, most multi-objective optimization algorithms encounter difficulties in solving many-objective optimization problems because they cannot balance convergence and diversity. As the number of objectives increases, the non-domin...
The paper is dedicated to the multi-criteria choice of an optimal variant of a pressure relief valve with a nominal pressure of 3 bar, manufactured from four different materials. The paper includes the usage of a number of existing methods that are c...
In the context of the global energy transition and China’s “double carbon” strategy, power demand continues to grow, leading to expanded power plant construction that faces challenges such as spatial resource conflicts and multi-obj...
To serve customized option selection for civil aircraft, a mathematical product option selection optimization model combined with an Improved Non-dominated Sorting Genetic Algorithm for decreasing aircraft fleet maintenance cost was investigated. For...
With the popularization of internet of things (IoT), the energy consumption of mobile edge computing (MEC) servers is also on the rise. Some important IoT applications, such as autonomous driving, smart manufacturing, and smart wearables, have high r...
Changes in object morphology can be quantified using 3D optical scanning to generate 3D models of an object at different time points. This process requires registration techniques that align target and reference 3D models using mapping functions base...
A major scientific objective of cognitive neuroscience is to define cortico-cortical functional connections supporting cognitive functions. Here, we use an original approach combining frequency-tagging and direct electrical stimulation (DES) to test...
In order to maximize the mixing performance of a micromixer with an integrated three-dimensional serpentine and split-and-recombination configuration, multi-objective optimizations were performed at two different Reynolds numbers, 1 and 120, based on...
Iterative reconstruction of density pixel images from measured projections in computed tomography has attracted considerable attention. The ordered-subsets algorithm is an acceleration scheme that uses subsets of projections in a previously decided o...
Solar energy is an important source of clean energy to combat climate change issues that motivate the establishment of solar farms. Establishing solar farms has been considered a proper alternative for energy production in countries like Mozambique,...
This paper introduces an evolutionary algorithm for n-dimensional single objective optimization problems: One-Dimensional Subspaces Optimization Algorithm (1D-SOA). The algorithm starts with an initial population in randomly selected positions. For e...
In this paper, we used multi-objective optimization in the exploration of unknown space. Exploration is the process of generating models of environments from sensor data. The goal of the exploration is to create a finite map of indoor space. It is co...
Bayesian Optimization (BO) provides an efficient framework for optimizing expensive black-box functions by employing a surrogate model (typically a Gaussian Process) to approximate the objective function and an acquisition function to guide the searc...
This study proposes a method for optimally selecting the operating parameters of an energy storage system (ESS) for frequency regulation (FR) in an electric power system. First, the method allows the optimal objective function of the selected paramet...
Renting is, like owning a house, a way to realize residence rights, playing an important role in maintaining the equilibrium of the housing market. The lack of attention paid to policy design of the rental housing market causes low effectiveness in t...
Remote sensing image object detection has been studied by many researchers in recent years using deep neural networks. However, optical remote sensing images contain many scenes with small and dense objects, resulting in a high rate of misrecognition...
According to the established model of a single resonance energy selective electron refrigerator with heat leakage in the previous literature, this paper performs multi-objective optimization with finite-time thermodynamic theory and NSGA-II algorithm...
The proportion of universal segment in tunnel construction is constantly increasing. A key factor affecting the quality of tunnel construction is the selection of the shield segment assembly points. Nevertheless, the quality and efficiency of the cur...
This study proposes a multi-objective stand structure optimization scheme based on deep reinforcement learning, demonstrating the strengths of deep reinforcement learning in solving multi-objective optimization problems and providing innovative insig...
Evolutionary algorithms, inspired by natural evolution, aim to optimize difficult objective functions without computing derivatives. Here we detail the relationship between classical population genetics of quantitative traits and evolutionary optimiz...
In recent years, scheduling optimization has been utilized in production systems. To construct a suitable mathematical model of a production scheduling problem, modeling techniques that can automatically select an appropriate objective function from...
Feature selection has been widely used in machine learning and data mining since it can alleviate the burden of the so-called curse of dimensionality of high-dimensional data. However, in previous works, researchers have designed feature selection me...
Since the fuzzy local information C-means (FLICM) segmentation algorithm cannot take into account the impact of different features on clustering segmentation results, a local fuzzy clustering segmentation algorithm based on a feature selection Gaussi...
In recent years, air emergency rescue capabilities have become increasingly important as an indicator of national comprehensive strength and development status. Air emergency rescue performs an indispensable role in addressing social emergencies by v...
We develop a sampling-type algorithm for localizing a small object from scattering parameter data measured in a bistatic configuration. To this end, we design a sampling-type imaging function based on the integral equation formula for the scattering...
This research addresses the two-dimensional strip packing problem to minimize the total strip height used, avoiding overlapping and placing objects outside the strip limits. This is an NP-hard optimization problem. We propose a greedy randomized adap...
Many real-world expensive industrial and engineering multi-objective optimization problems (MOPs) are driven by historical, experimental, or simulation data. In such scenarios, due to the expensive cost and time required, we are only left with a smal...
At present, the traditional magnetic three-dimensional inversion method has been fully developed and is widely used. Magnetic exploration is a kind of geophysical exploration method that uses the magnetic field changes (magnetic anomalies) caused by...
The choice of which objective functions, or benchmark problems, should be used to test an optimization algorithm is a crucial part of the algorithm selection framework. Benchmark suites that are often used in the literature have been shown to exhibit...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an information-theoretic approach that is robust to multicolinearity problem. It uses an objective function that is the sum of the entropies for coefficie...
Stream gauge stations are facilities for measuring stream water levels and flow rates, and their main purpose is to produce the data required to analyze hydrological phenomena. However, there are no specific criteria for selecting the locations and i...
The effective resolution of constrained multi-objective optimization problems (CMOPs) requires a delicate balance between maximizing objectives and satisfying constraints. Previous studies have demonstrated that multi-swarm optimization models exhibi...
In the Web of Things (WoT) context, an increasing number of stationary and mobile objects provide functions as RESTful services, also called resources, that can be combined with other existing Web resources, to create value-added processes. However,...
Based on the quadrilateral heat generation body (HGB) proposed by previous literature, the multi-objective constructal design is performed. Firstly, the constructal design is performed by minimizing the complex function composed of the maximum temper...
This paper proposes a methodology for the layout selection of an urban drainage system as an extension to the methodology for an optimal sewer network design proposed by Duque, Duque, Aguilar, & Saldarriaga. The layout selection approach proposed...
In this paper, we proposed a method for matching the color and glossiness of an object between different displays by using tone mapping. Since displays have their own characteristics, such as maximum luminance and gamma characteristics, the color and...
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