The concentration of dissolved oxygen (DO) in seawater is a core ecological indicator in aquaculture, and its accurate prediction is of great value for the management of marine ranching. In response to the lack of exploration on the optimization mech...
Damage detection and system identification with output-only information is an important but challenging task for ensuring the safety and functionality of civil structures during their service life. In this paper, a relatively simple and efficient ite...
Ensuring precise prediction, monitoring, and control of frictional contact temperature is imperative for the design and operation of advanced equipment. Currently, the measurement of frictional contact temperature remains a formidable challenge, whil...
This paper studies the trajectory tracking control problem of an Air Cushion Vehicle (ACV) with yaw rate error constraint, input effective parameters, model uncertainties and external wind disturbance. Firstly, based on the four-degree of freedom (DO...
The study of cellular structures and their properties represents big potential for their future applications in real practice. The article aims to study the effect of input parameters on the quality and manufacturability of cellular samples 3D-printe...
Rockfalls present a significant hazard to human activities; therefore, their identification and knowledge about potential spatial impacts are important in planning protection measures to reduce rockfall risk. Remote sensing with unmanned aerial vehic...
The paper presents results and sensitivity analysis of the results of a real detailed study focused on changes in water consumption and its unevenness with changing pressure conditions in a particular observed office building. The dependence of water...
This paper addresses the problem of parameter identification for discrete-time stochastic systems with unknown exogenous inputs. These systems form an important class of dynamic stochastic system models used to describe objects and processes under a...
This paper investigates the observer-based consensus control problem for linear parameter-varying (LPV) multi-agent systems (MASs) with unknown inputs. Firstly, an interval observer (IO) is designed to generate the state interval estimation for each...
In this paper, a novel method is proposed to design a free final time input signal, which is then used in the robust system identification process. The solution of the constrained optimal input design problem is based on the minimization of an extra...
This paper presents an Automatic Ball-Balancing Mechatronic System (ABMS) with a lever transmission, which provides higher positioning accuracy for the ball. The system was identified by a double integrator, and the results confirmed the suitability...
This paper presents theoretical and experimental research studying the influence of process parameters on the quality of biomass pellets. A validated mathematical model was developed, expressing the density of biomass pellets as determined by moistur...
15 December 2020
Background: Assessment of uncertainty in cost-effectiveness analyses (CEAs) is paramount for decision-making. Probabilistic sensitivity analysis (PSA) estimates uncertainty by varying all input parameters simultaneously within predefined ranges; howe...
The process of electrospinning is subject to a variety of input parameters ranging from the characterization of polymers and solvents, the resulting solutions, the geometrical configuration of the device, including its process parameters, and ending...
Aleatoric and epistemic uncertainties can be represented probabilistically in mechanical systems. However, the distribution parameters of epistemic uncertainties are also uncertain due to sparsely available or inaccurate uncertainty information. Ther...
For engineering products with uncertain input variables and distribution parameters, a sampling-based sensitivity analysis methodology was investigated to efficiently determine the influences of these uncertainties. In the calculation of the sensitiv...
This paper deals with the design of a complete state control for input unsigned, rank deficient matrix parameters of a linear system with system dynamics defined by ostensible structures of Metzler matrices. The proposed solution is based on the prin...
In this study, an uncertainty quantification (UQ) and sensitivity analysis (SA) workflow was developed for the input parameters of the CANDLE module, which is currently being tested and verified for calculating the downward relocation and solidificat...
The paper deals with the issue of determining the optimal setting of input variables in Ansys CFX for modeling pump flow in turbine operation (PAT). The pump model was created in Autodesk Inventor. The mesh for numerical simulations was created using...
The technology of casting with crystallization under pressure-squeeze casting belongs to unconventional pressure-casting methods. The melt or material in a semi-solid state is pressed under pressure until the casting solidifies completely. The input...
This study proposes an optimal design approach for an inverter-fed permanent magnet synchronous motor (PMSM) considering the variation in motor control parameters and input voltage (inverter output voltage), which vary with respect to the temperature...
This paper presents an auto-tuning approach for dual-input power amplifiers using a combination of global optimisation search algorithms and adaptive linearisation in the optimisation of a multiple-input power amplifier. The objective is to exploit t...
The purpose of this paper is to study how input parameters affect the dynamic characteristics and electric consumption characteristics of an electric motorcycle. To achieve this goal, a simulation model of the electric motorcycle, including dynamic m...
The identification of the most rockfall-prone areas is the first step of the risk assessment procedure. In the case of land and urban planning, hazard and risk analyses involve large portions of territory, and thus, preliminary methods are preferred...
Compared with traditional deepwater drilling, riserless mud recovery (RMR) drilling technology has the advantages of improving drilling efficiency, reducing risks, and minimizing environmental effects. Therefore, RMR drilling technology has been wide...
We present a sensitivity analysis on the impact of input parameters and methods used on the results of a probabilistic seismic hazard assessment (PSHA). The accurate estimation of the parameters in recurrence models (declustering and fitting methods)...
This work focuses on the finite-time synchronization control (FTSC) for fractional-order chaotic systems (FOCSs) subject to uncertain dynamics, unknown parameters and input nonlinearities. In the control law design, the uncertain dynamics of the FOCS...
A tremendous amount of work has been done in the recent years in the optimization of input parameters, however, current optimization techniques can only provide a single optimal input process parameter combination. Although alternative techniques hav...
Despite the apparent stability of the electricity system from a consumer’s point of view, there is indeed significant effort exerted by network operators to guarantee the constancy of the electricity supply in order to meet demands any time. In...
In this study, an artificial neural network (ANN) was established to predict product properties (mass, diameter, height) using six process conditions of the injection-molding process (melt temperature, mold temperature, injection speed, packing press...
Digitally controlled Dual-Input Doherty Power Amplifiers (DIDPAs) are becoming increasingly popular due to the flexible input signal splitting between the main and auxiliary stages. Nevertheless, the presence of many degrees of freedom, e.g., input a...
In recent years, glass has been a largely used material for load-bearing or non-structural components in buildings and constructions. For this reason, dedicated calculation methods and approaches are required for the major loading and boundary condit...
Microwave remote sensing can measure surface geometry. Via the processing of the Synthetic Aperture Radar (SAR) data, the earth surface geometric parameters can be provided for geoscientific studies, especially in geological mapping. For this purpos...
Decentralized energy systems and local renewable energy generation are playing an increasingly important role in ensuring an efficient, sustainable, and resilient energy supply at the distribution grid and district levels. Sector-coupled energy syste...
Active power factor correction converters are often introduced as the front stage of power electronic equipment to improve the power factor and eliminate higher harmonics. A Boost or Buck-Boost converter operating in discontinuous current mode is alw...
This study presents a vehicle mass estimation system based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested real-time methodology is based on the explicit correlation between r...
The performance of artificial neural networks (ANNs) is highly influenced by the selection of input variables and the architecture defined by hyper parameters such as the number of neurons in the hidden layer and connections between network variables...
Intelligent geoprocessing relies heavily on formalized parameter constraints of geoprocessing tools to validate the input data and to further ensure the robustness and reliability of geoprocessing. However, existing methods developed to formalize par...
This article presents comprehensive typology of all possible relationships among inputs of an economic system, their productivity, and output. Each situation is given an exact name explaining how intensive and extensive factors contributes to the sys...
The quality of measuring datasets of the thermal response test (TRT) significantly influences the interpretation of borehole thermal parameters (BTP). A thermal response test with an unstable power input may induce an unacceptable error in the estima...
As is widely known, additive manufacturing (AM) allows very complex parts to be manufactured with porous structures at a relatively low cost and in relatively low manufacturing times. However, it is necessary to determine in a precise way the input v...
Herein, two novel Physics Informed Neural Network (PINN) architectures are proposed for output-only system identification and input estimation of dynamic systems. Using merely sparse output-only measurements, the proposed PINNs architectures furnish...
Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product q...
This paper studies the robust
A Long Short Term Memory (LSTM) based sales model has been developed to forecast the global sales of hotel business of Travel Boutique Online Holidays (TBO Holidays). The LSTM model is a multivariate model; input to the model includes several indepen...
This paper presents a new indirect tire pressure monitoring system (TPMS) based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested methodology is based on the explicit correlatio...
Wire Arc Additive Manufacturing (WAAM) has emerged as a promising additive manufacturing technique due to its high deposition rate and low material cost. WAAM is increasingly adopted in various industries for the production of large-scale metal compo...
Accurate and reliable dam inflow prediction models are essential for effective reservoir operation and management. This study presents a data-driven model that couples a long short-term memory (LSTM) network with robust input predictor selection, inp...
Recently, a quasi-fractional order gradient descent (QFGD) algorithm was proposed and successfully applied to solve system identification problem. The QFGD suffers from the overparameterization problem and results in estimating the redundant paramete...
In this study, a dual-input coupling powertrain system (DICPS) was proposed to improve the energy utilization efficiency of pure electric tractors (PETs). The working principles of the DICPS under different modes were analyzed and dynamic models were...
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