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Automated recognition of spacecraft and space debris using imaging plays an important role in securing space safety and space exploration. Although deep learning is now the most successful solution for image-based object classification, it requires a myriad number of training data, which are not available for most real applications. In this paper, we investigate different single and hybrid data augmentation...
Predictive analytics and data fusion techniques are being regularly used for analysis in Quantitative Risk Management (QRM). The primary risk metric of interest, Value-at-Risk (VaR), has always been difficult to robustly estimate for different data types. The classical Monte Carlo simulation (MCS) approach (denoted henceforth as classical approach) assumes the independence of loss severity and loss...
In the multiple target tracking scenarios, the correct matching between targets and measurements is critical. There have been many approaches to resolve this problem called data association. In this paper, a regression method is proposed to resolve the data association problem. In the logistic regression model, nine potential predictor variables are designed which are related to the geometric information...
Big classes of directional distribution laws generalizing the von Mises distribution are provided in [4] following a general geometric offset approach in [20]. Once a distribution law is estimated for modeling a given data set, one of the next steps of statistical analysis is simulating from such distribution. The von Mises distribution was simulated in [1] using an acceptance-rejection simulation...
Dempster-Shafer evidence theory (DST) is a theoretical framework for uncertainty modeling and reasoning. The determination of basic belief assignment (BBA) is crucial in DST, however, there is no general theoretical method for BBA determination. In this paper, a method of generating BBA using fuzzy numbers is proposed. First, the training data are modeled as fuzzy numbers. Then, the dissimilarities...
This paper describes a study on modelling the Received Signal Strength Indicator (RSSI) measured by the smartphone of a vehicle user. The present transmissions are emitted by dedicated radio frequency sources, such as Bluetooth Low Energy (BLE) beacons, mounted to the vehicle to determine the driver/passenger(s) proximity or relative position(s). Based on empirical data, a model of the measurements...
In current interval-valued linear regression models, meaningless predictions may be generated because the lower bounds of the predicted intervals may be greater than their upper bounds. To avoid this problem, we propose a constrained interval-valued linear regression model based on random set theory. However, due to the introduction of constraints in this model, the expectation of the errors is no...
Neuro-Fuzzy has been successfully applied in the malware detection from before. It gives flexibility in building an effective and human understandable rule-based detection model. Fuzzy variables consist of linguistic terms that are constructed based on the characteristics of the corresponding numerical features. This gives a level of abstraction that allows controlling the distribution drift and maintaining...
A coal mine rescue snake robot with four orthogonal joints is developed. Taking the robot as an experimental platform, aiming at how to model and identify the environment of the coal mine tunnel after the disaster, a multi sensor data fusion algorithm based on genetic algorithm optimization of the variable structure fuzzy neural network (GAFNN) is proposed. Firstly, the fuzzy neural network model...
Situational understanding (SU) requires a combination of insight — the ability to accurately perceive an existing situation — and foresight — the ability to anticipate how an existing situation may develop in the future. SU involves information fusion as well as model representation and inference. Commonly, heterogenous data sources must be exploited in the fusion process: often including both hard...
Situational Awareness (SAW) is a widespread concept in areas that require critical decision-making and refers to the level of consciousness that an individual or team has about a situation. A poor SAW can induce humans to failures in the decision-making process, leading to losses of lives and property damage. Data fusion processes present opportunities to enrich the knowledge about situations by integrating...
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