A continuous optimization framework for hybrid system identification
نویسندگان
چکیده
منابع مشابه
A continuous optimization framework for hybrid system identification
We propose a new framework for hybrid system identification, which relies on continuous optimization. This framework is based on the minimization of a cost function that can be chosen as either the minimum or the product of loss functions. The former is inspired by traditional estimation methods, while the latter is inspired by recent algebraic and support vector regression approaches to hybrid...
متن کاملA General Direct Weight Optimization Framework for Nonlinear System Identification
The direct weight optimization (DWO) approach is a method for finding optimal function estimates via convex optimization, applicable to nonlinear system identification. In this paper, an extended version of the DWO approach is introduced. A general function class description — which includes several important special cases — is presented, and different examples are given. A general theorem abou...
متن کاملA Hybrid Framework for Building an Efficient Incremental Intrusion Detection System
In this paper, a boosting-based incremental hybrid intrusion detection system is introduced. This system combines incremental misuse detection and incremental anomaly detection. We use boosting ensemble of weak classifiers to implement misuse intrusion detection system. It can identify new classes types of intrusions that do not exist in the training dataset for incremental misuse detection. As...
متن کاملA Hybrid Modeling for Continuous Casting Scheduling Problem
This paper deals with a multi-agent-based interval type-2 fuzzy (IT2F) expert systemfor scheduling steel continuous casting. Continuous caster scheduling is a complex and extensiveprocess that needs expert staff. In this study, a distributed multi-agent-based structure is proposed as asolution. The agents used herein can cooperate with each other via various communication protocols.To facilitat...
متن کاملHybrid Evolutionary Computation for Continuous Optimization
Hybrid optimization algorithms have gained popularity as it has become apparent there cannot be a universal optimization strategy which is globally more beneficial than any other. Despite their popularity, hybridization frameworks require more detailed categorization regarding: the nature of the problem domain, the constituent algorithms, the coupling schema and the intended area of application...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Automatica
سال: 2011
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2011.01.020