System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these...
Spray drying is a single step process in which solutions or dispersions are converted into dry particles. It is widely used in pharmaceutical technology to produce inhalable particles. Dry particle behavior during inhalation, described as the emitted...
The purpose of this study is to employ and improve evolutionary algorithms, namely the genetic algorithm (GA) and the differential evolution algorithm (DE), to extract the parameters of the equivalent circuit model (ECM) of a bifacial photovoltaic mo...
In this article, the optimization of a realistic oil and gas separation plant has been studied. Using Latin Hypercube Sampling (LHS) and rigorous process simulations, surrogate models using Kriging have been established for selected model responses....
In this paper, we present a survey about the latest results in global stability concerning the discrete-time evolutionary Ricker competition model with n species, in both, autonomous and periodic models. The main purpose is to convey some arguments a...
Evolution of an individual within another individual is known as within-host dynamics (WHD). The most common modeling technique to study WHD involves ordinary differential equations (ODEs). In the field of biology, models of this kind assume, for exa...
In this paper, we study the local, global, and bifurcation properties of a planar nonlinear asymmetric discrete model of Ricker type that is derived from a Darwinian evolution strategy based on evolutionary game theory. We make a change of variables...
Within the mind, there are a myriad of ideas that make sense within the bounds of everyday experience, but are not reflective of how the world actually exists; this is particularly true in the domain of science. Classroom learning with teacher explan...
The use of a genetic algorithm in evolutionary design is one of the major generative approaches for synthesis and evaluation during the design process. The process stimulates creativity in generating new, unexpected artifacts and aiding in their eval...
We introduce a model for studying the evolutionary dynamics of Poker. Notably, despite its wide diffusion and the raised scientific interest around it, Poker still represents an open challenge. Recent attempts for uncovering its real nature, based on...
This paper introduces an Evolutionary Computing Control Strategy (ECCS) for the motion control of nonholonomic robots, and integrates an ordinary differential equation (ODE)-based kinematics model with a nonlinear model predictive control (NMPC) stra...
Interactive evolutionary algorithms (IEAs) coupled with a data-driven user surrogate model (USM) have recently been proposed for enhancing personalized recommendation performance. Since the USM relies on only one model to describe the full range of u...
Mobile crowdsensing (MCS) is a way to use social resources to solve high-precision environmental awareness problems in real time. Publishers hope to collect as much sensed data as possible at a relatively low cost, while users want to earn more reven...
Ovarian cancer (OC) is a common reason for mortality among women. Deep learning has recently proven better performance in predicting OC stages and subtypes. However, most of the state-of-the-art deep learning models employ single modality data, which...
Community detection is widely recognized as a crucial area of research in network science. In recent years, multi-objective evolutionary algorithms (MOEAs) have been extensively employed in community detection tasks. Continuous coding is able to tran...
In recent years, financial fraud of listed internet companies has emerged one after another. Under the strategic goal of full audit coverage, the problems caused by audit failure have attracted more and more attention in China. We use the bounded rat...
Network environments have recently emerged as a considerable research area. In addition to government supervision, platform supervision is also critical to improve network environments. So, we should improve the social network platform’s single...
Distributed hydrological models based on shallow water equations have gained popularity in recent years for the simulation of storm events, due to their robust and physically based routing of surface runoff through the whole catchment, including hill...
The frog-in-the-pan (FIP) phenomenon suggests that investors are more sensitive to abrupt price changes than gradual price changes in the stock market. Based on the cognitive-evolutionary model of surprise and the reinforcement learning model, this p...
This article deals with the problem of designing regression models for evaluating the parameters of the operation of complex technological equipment—hydroturbine units. A promising approach to the construction of regression models based on nonparamet...
The combination and convergence of energy-intensive industries developed by ecological factors based on energy clusters is discussed in this paper. Here, a few models for the prediction of greenhouse effects are used as a single type of modeling. In...
27 February 2020
This paper first portrays the equilibrium payoff of enterprise’s cooperation of environmental governance based on the Cournot model. Secondly, the evolutionary game model in complex networks is adopted to depict the evolution of environmental g...
In the context of expensive constraint multi-objective problems, it is evident that the feasible domain shapes and sizes of different problems vary considerably. The difficulty in finding optimal solutions presents a significant challenge in ensuring...
Multi-satellite imaging mission planning (MSIMP) is an important focus in the field of satellite application. MSIMP involves a variety of coupled constraints and optimization objectives, which often require extensive simulation and evaluation when so...
An algorithm based on the human evolutionary model is proposed for solving nonlinear bilevel programing problems. In view of the hierarchical structure of this problem, the algorithm is designed through feeding back the optimal solution of the lower-...
The behavioral choices and speculative psychology of the participants in medical waste disposal can lead to the evolution of the medical waste disposal crisis, which has a great impact on and represents a potential threat to environmental safety as w...
We investigate the robustness of adaptive chemotherapy schedules over repeated cycles and a wide range of tumor sizes. Using a non-stationary stochastic three-component fitness-dependent Moran process model (to track frequencies), we quantify the var...
Thanks to their peculiar features, organic transistors are proving to be a valuable alternative to traditional semiconducting devices in several application fields; however, before releasing their exploitation, simulating their behaviour through adeq...
Meta-heuristic algorithms are the dominant techniques for parameter estimating for solar photovoltaic (PV) models. Current algorithms are primarily designed with a focus on search performance and convergence speed, but they fail to account for the si...
Meteorological drought is a common hydrological hazard that affects human life. It is one of the significant factors leading to water and food scarcity. Early detection of drought events is necessary for sustainable agricultural and water resources m...
Evolutionary and ecological processes are primary drivers of ecological network constrictions. However, the ways that these processes underpin self-organization and modularity in networks are poorly understood. Here, we performed network analyses to...
Temporal knowledge graphs play an increasingly prominent role in scenarios such as social networks, finance, and smart cities. As such, research on temporal knowledge graphs continues to deepen. In particular, research on temporal knowledge graph rea...
To solve the problems of economic growth and environmental pollution in China, it is crucial for local governments, as the responsible body for environmental protection, to rely on digital technology platforms to promote the green transformation of m...
Energy storage technology plays a significant role in the pursuit of the high-quality development of the electricity market. Many regions in China have issued policies and regulations of different intensities for promoting the popularization of the e...
The nonlinearity nature of land subsidence and limited observations cause premature convergence in typical data assimilation methods, leading to both underestimation and miscalculation of uncertainty in model parameters and prediction. This study foc...
Ontology is the kernel technique of the Semantic Web (SW), which models the domain knowledge in a formal and machine-understandable way. To ensure different ontologies’ communications, the cutting-edge technology is to determine the heterogeneo...
In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digita...
The complexity and uncertainty of engineering construction present significant challenges to construction safety. Smart sites are an important measure of the transformation and upgrading of China’s construction industry. In the context of smart...
Pharmaceuticals play a critical role in the eradication of infectious diseases. Effective pharmaceutical inventory management is important for controlling epidemics since medical resources such as pharmaceuticals, medical staff, and hospitals are lim...
Energy and the environment are important foundations for sustainable economic development. In order to realize the sustainable development of energy economy, clarify the respective responsibilities of the government and enterprises, and explore the i...
The collapse settlement of granular soil, which brings about considerable deformations, is an important issue in geotechnical engineering. Several factors are involved in this phenomenon, which makes it difficult to predict. The present study aimed t...
The Mixed No-Idle Permutation Flow Shop Scheduling Problem (MNPFSSP) represents a specific case within regular flow scheduling problems. In this problem, some machines allow idle times between consecutive jobs or operations while other machines do no...
The utilization of conventional energy sources commonly leads to heightened energy consumption and the generation of specific forms of environmental pollution. As an innovative power management and dispatch system, virtual power plants (VPPs) have th...
The green renovation of existing residential buildings is a key way for the construction industry to achieve sustainable development and the dual carbon goals of China, which makes it urgent to make collaborative decisions among multiple stakeholders...
Almost all published rooting and dating studies on SARS-CoV-2 assumed that (1) evolutionary rate does not change over time although different lineages can have different evolutionary rates (uncorrelated relaxed clock), and (2) a zoonotic transmission...
Conventional deep learning models rely heavily on the McCulloch–Pitts (MCP) neuron, limiting their interpretability and biological plausibility. The Dendritic Neuron Model (DNM) offers a more realistic alternative by simulating nonlinear and co...
Neuropterida is a super order of Holometabola that consists of the orders Megaloptera (dobsonflies, fishflies, and alderflies), Neuroptera (lacewings) and Raphidioptera (snakeflies). Several proposed higher-level relationships within Neuropterida, su...
Neuropeptides are biomolecules with crucial physiological functions. Accurate identification of neuropeptides is essential for understanding nervous system regulatory mechanisms. However, traditional analysis methods are expensive and laborious, and...
Recently, evolutionary algorithms that can efficiently solve decomposable binary optimization problems have been developed. They are so-called model-based evolutionary algorithms, which build a model for generating solution candidates by applying a m...
This study introduces a theoretical and computational framework for modeling acoustic wave propagation in defective concrete, with applications to non-destructive testing and structural health monitoring. The formulation is based on a coupled system...
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