{'fraction_non_alphanumeric': 0.01729559748427673, 'fraction_numerical': 0.0, 'mean_word_length': 5.56701030927835, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Identification of IP packet transmission time series using neuro-fuzzy techniques

In this paper we are interested to applied the adaptive neuro-fuzzy inference system (ANFIS) technique, which is realized by an appropriate combination of fuzzy systems and neural networks, for identifying and forecasting a set of input and output data of packet transmission over internet protocol (IP) networks. The obtained results demonstrate that the developed model presents the same statistical characteristics as those really observed. This model fits well real data and provides an effective description of network condition at different times.