Papers by Keyword: Estimation

Abstract: In recent decades, relative humidity has become a research topic that has received increasing attention due to its important role in climate change and global warming. One of the most typical issues with relative humidity is data loss due to instrument deterioration. This research attempts to apply feature selection and hyperparameter tuning methods as an approach to optimizing the reliability of the multilayer perceptron (MLP) model to predict relative humidity values designed into the MLP-CV framework. The coefficient of determination (R²), root mean squared error (RMSE), and absolute error (MAE) are used to determine the model's correctness. The results showed that the MLP-CV model had better accuracy compared to the MLP model for predicting relative humidity missing values, with R² = 0.788, RMSE = 1.838, and MAE = 1.431.

Abstract: In this article, we are interested in identifying the parameters of an aerobic bioprocess modelused for wastewater treatment. In the field of biotechnology, various computer bugs caused by roundingerrors can induce an error interval that is too wide during data acquisition. For this reason, weare testing a new identification method using a set method based on interval arithmetic. The processstudied is the chemical transformation of ammoniacal nitrogen which takes place in two stages: Reactionof nitrificationdenitrification.The parameters chosen for the identification are the yields andthe maximum growth rates. Initially, the study of observability by a differential algebraic method willsimplify the study of the mathematical model. This nonlinear model is described by six differentialequations. Subsequently, we apply a set method, in particular the propagation of constraints also calledforwardbackward propagation, this technique allowed us to determine intervals containing the variablereturns as well as the maximum specific growth rates defined from the Monod model which describesthe operation of the bioreactor. This method also guarantees the result by rejecting all inconsistentvalues.

Abstract: The Simulation of Crowd Sensing in Closed Space with the Attenuation Measurement of the Wi-Fi Signal is Proposed here. A Train Car is Used as the Test Environment of Interest. Experimental Validation is Performed for a Certain Range of Input Parameters which Include Permittivity of Human Body, Structure Materials and Sensor Placements. the Simulation Results Show that for all Cases, the Signal Strengths Associated with Masses of Human Body Reduce with Number of Passengers. the Number of Passengers can Be Estimated with Good Accuracy Using Linear Function with the R-Square Value over 0.97 and RMSE Value below 2. the Simulation Results Suggest that the Estimation Accuracy of Number of Passengers will Improve with Higher Number of Passengers and Multiple Transmitters in Neighbor Nodes can Affect the Overall Precision. the Experimental Validation Exhibits the same Trend as that of the Simulation. the Additional Experiment Indicates that the Passenger Body Movement Also has a Considerable Impact on the Estimation Accuracy.

Abstract: SIGMA-class warship one of warship type is designed up to sea state 6. The ship was redesigned in enlarged dimensions, and called SIGMA extended class warships. A control system can give a performance of response in accordance to the set point when the value of controlled variable can be transmitted to the controller accurately. The characteristic of sensor is not usually able to tranmit a proper value, due to the noise on the sensor and also the environment disturbances. This paper describe a strategy of Kalman filter to estimate variables controlled when the presence noise on the compass or gyrocompas. The result of Kalman filter implementations give the magnitude of the integral absolute error of yaw and sway less than 5%, when there are noise on the measurement and the disturbances.

Abstract: This paper introduces a method for in-process tool wear estimation of an air turbine spindle, which is equipped with a rotation control system for ultra-precision milling. Previous investigations revealed that the pressure of the compressed air for supply that is used to control the rotational speed and tool wear at the time when steady wear occurs, maintains a linear relationship when processing SKD61 steel. In addition, the extent to which the supply pressure changed was reduced after chipping occurred. Therefore, the possibility exists that the tool wear can be estimated by obtaining the supply pressure during processing. The purpose of this paper is to propose the evaluation of an in-process tool wear estimation method, and to evaluate its validity. An estimation method is necessary as this would allow the amount of tool wear to be estimated and abnormal wear of occurrence to be detected. Because of the linear relationship between the air pressure and the amount of tool wear, the latter can be estimated by plotting the approximately linear relationship of the tool wear as a function of the air pressure. The proposed estimation method for processing the results obtained for SKD61, is capable of estimating the relative error of the measured value within 0.2 against the estimated value at the time. Furthermore, the occurrence of abnormal wear is determined from the amount of change in the supply pressure. Thus, SKD11 steel was processed for the proposed estimation method to verify whether it is valid for cutting high hardness steel. As a result, for SKD11 the estimation method produced estimation results similar to those obtained for SKD61. Therefore, the suggested estimation method is likely to be effective for high-hardness steel cutting.

Abstract: Present paper deals with the experimental investigation of static modulus of elasticity of hardened concrete and its relation to compressive strength of concrete. Based on the number of measurement was derived expression of dependence of modulus of elasticity on compressive strength of concrete which was determined using cubic specimens; modulus of elasticity was measured using prismatic specimens of dimensions 100x100x400 mm. Studied concrete mixtures present commonly used concrete of all established strength classes.

Abstract: At present, manual method for acquiring discontinuity 2D density is inefficient and error-prone. This paper proposes a digital method based on 3D digital traces model. And Mauldon method has been chosen to estimate 2D density comparing with Kulatilake and Wu method. It makes study on 2D density much more convenient. The results of study with this method show feasibility and efficiency of the new method and Mauldon method for estimating has been tested to be accurate in this paper.

Abstract: A filter/guidance simulation toolbox based on Matlab software was designed. Built under the principle of “define once and use many times”, the propose toolbox successfully separate the estimation algorithms, the guidance law, and the math model under investigation into three different yet related parts, which drastically reduced the burden of repeatedly designing the same filters and guidance law for different simulation models. Typical example from both simulation cases and real field test data proved the correctness and effectiveness of the proposed toolbox.

Abstract: This paper investigates the estimation of optical amplifiers based on an optoelectronic equivalent model. In order to improve the estimation performance with the limited information, a linear filter is adopted. The limited information can be treated as a switch that acts in a random manner. As the switch is open, the corresponding output is held at the previous value. The estimation of optical amplifiers taking into account the limited information can give out the better results. The results demonstrate the effectiveness and applicability.

Abstract: s: this text puts forward the estimation process of typical linear regression model first, then, puts forward the establishment of fuzzy linear regression model based on it. At last, in enterprise manufacturing’ estimation, passing contrast application analysis to explained the advantage of fuzzy linear regression model.