Πλοήγηση ανά Συγγραφέα "Hilas, Constantinos"
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Τεκμήριο A computational intelligence-based forecasting system for telecommunications time series(2012-02) Mastorocostas, Paris; Hilas, ConstantinosIn this work a computational intelligence-based approach is proposed for forecasting outgoing telephone calls in a University Campus. A modified Takagi–Sugeno–Kang fuzzy neural system is presented, where the consequent parts of the fuzzy rules are neural networks with an internal recurrence, thus introducing the dynamics to the overall system. The proposed model, entitled Locally Recurrent Neurofuzzy Forecasting System (LR-NFFS), is compared to well-established forecasting models, where its particular characteristics are highlighted.Τεκμήριο A generalized Takagi–Sugeno–Kang recurrent fuzzy-neural filter for adaptive noise cancelation(2008-10) Mastorocostas, Paris; Varsamis, Dimitris; Hilas, Constantinos; Mastorocostas, ConstantinosThis paper presents a recurrent fuzzy-neural filter for adaptive noise cancelation. The cancelation task is transformed to a system-identification problem, which is tackled by use of the dynamic neuron-based fuzzy neural network (DN-FNN). The fuzzy model is based on Takagi–Sugeno–Kang fuzzy rules, whose consequent parts consist of linear combinations of dynamic neurons. The orthogonal least squares method is employed to select the number of rules, along with the number and kind of dynamic neurons that participate in each rule. Extensive simulation results are given and performance comparison with a series of other dynamic fuzzy and neural models is conducted, underlining the effectiveness of the proposed filter and its superior performance over its competing rivals.Τεκμήριο A Recurrent Neural Network–based Forecasting System for Telecommunications Call Volume(2013-09-01) Mastorocostas, Paris; Hilas, Constantinos; Varsamis, Dimitris; Dova, StergianiA recurrent neural network–based forecasting system for telecommunications call volume is proposed in this work. In particular, the forecaster is a Block–Diagonal Recurrent Neural Network with internal feedback. Model’s performance is evaluated by use of real–world telecommunications data, where an extensive comparative analysis with a series of existing forecasters is conducted, including both traditional models as well as neural and fuzzy approaches.Τεκμήριο A study on the security, the performance and the penetration of wi-fi networks in a greek urban area(IFIP International Federation for Information Processing, 2011) Mousionis, Savvas; Vakaloudis, Alex; Hilas, ConstantinosThis paper presents a study on the expansion of urban Wi-Fi networks and the degree of users’ awareness about their characteristics. It involves an experiment contacted at the area of Serres, a Greek city of around 70,000 inhabitants. The findings revealed that although the number of Wi-Fi networks is quite high, their owners are unaware of their technical settings. As a result many networks remain either unlocked or with WEP encryption while many adjacent networks use the same channel thus reducing their performance.