Search results for "mathematics"
showing 10 items of 22031 documents
Input Selection Methods for Soft Sensor Design: A Survey
2020
Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …
P-FCM: a proximity-based fuzzy clustering for user-centered web applications
2003
Abstract In last years, the Internet and the web have been evolved in an astonishing way. Standard web search services play an important role as useful tools for the Internet community even though they suffer from a certain difficulty. The web continues its growth, making the reliability of Internet-based information and retrieval systems more complex. Nevertheless there has been a substantial analysis of the gap between the expected information and the returned information, the work of web search engine is still very hard. There are different problems concerning web searching activity, one among these falls in the query phase. Each engine provide an interface which the user is forced to le…
Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations
2020
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…
Dissipativity-Based Small-Gain Theorems for Stochastic Network Systems
2016
In this paper, some small-gain theorems are proposed for stochastic network systems which describe large-scale systems with interconnections, uncertainties and random disturbances. By the aid of conditional dissipativity and showing times of stochastic interval, small-gain conditions proposed for the deterministic case are extended to the stochastic case. When some design parameters are tunable in practice, we invaginate a simpler method to verify small-gain condition by selecting one subsystem as a monitor. Compared with the existing results, the existence-and-uniqueness of solution and ultimate uniform boundedness of input are removed from requirements of input-to-state stability and smal…
Hard material small-batch industrial machining robot
2018
Abstract Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the developme…
Nonlinear statistical retrieval of surface emissivity from IASI data
2017
Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…
A note on best proximity point theory using proximal contractions
2018
In this paper, a reduction technique is used to show that some recent results on the existence of best proximity points for various classes of proximal contractions can be concluded from the corresponding results in fixed point theory.
Conditional Versus Joint Probability Assessments
1984
AbstractThe assessment of conditional and / or joint probabilities of events that constitute scenarios is necessary for sound planning, forecasting, and decision making. The assessment process is complex and subtle, and various difficulties are encountered in the elicitation of such probabilities such as, implicit violations ofthe probability calculus and some meaningfjilness conditions. The necessary and sufficient as well as meaningfulness conditions that the elicited information on conditional and joint probabilities must satisfy are evaluated against actual assessments empirically. A high frequency of violation of these conditions was observed in assessing both conditional and joint pro…
Aesthetic considerations for the min-max K-Windy Rural Postman Problem
2017
[EN] The aesthetic quality of routes is a feature of route planning that is of practical importance, but receives relatively little attention in the literature. Several practitioners have pointed out that the visual appeal of a proposed set of routes can have a strong influence on the willingness of a client to accept or reject a specific routing plan. While some work has analyzed algorithmic performance relative to traditional min-sum or min-max objective functions and aesthetic objective functions, we are not aware of any work that has considered a multi-objective approach. This work considers a multi-objective variant of the Min-Max K-Vehicles Windy Rural Postman Problem, discusses sever…
A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm
2013
Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…