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Sachin Gowda, Vaishakh Kunjar, Aakash Gupta, Govindaswamy Kavitha, Bishnu Kant Shukla and Parveen Sihag
In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional labora...
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Maryam Alzaid and Fethi Fkih
It is crucial to analyze opinions about the significant shift in education systems around the world, because of the widespread use of e-learning, to gain insight into the state of education today. A particular focus should be placed on the feedback from ...
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Imane Zaimi, Abdelali Boushaba, Mohammed Oumsis, Brahim Jabir, Moulay Hafid Aabidi and Adil EL Makrani
Reducing transmission traffic delay is one of the most important issues that need to be considered for routing protocols, especially in the case of multimedia applications over vehicular ad hoc networks (VANET). To this end, we propose an extension of th...
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Mohammed Madiafi, Jamal Ezzahar, Kamal Baraka and Abdelaziz Bouroumi
In this paper, we propose a new neural architecture for object classification, made up from a set of competitive layers whose number and size are dynamically learned from training data using a two-step process that combines unsupervised and supervised le...
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Cheng-Jian Lin, Min-Su Huang and Chin-Ling Lee
The applications of computer networks are increasingly extensive, and networks can be remotely controlled and monitored. Cyber hackers can exploit vulnerabilities and steal crucial data or conduct remote surveillance through malicious programs. The frequ...
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Hind R. Mohammed and Zahir M. Hussain
Accurate, fast, and automatic detection and classification of animal images is challenging, but it is much needed for many real-life applications. This paper presents a hybrid model of Mamdani Type-2 fuzzy rules and convolutional neural networks (CNNs) a...
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Deepaa Selva, Balakrishnan Nagaraj, Danil Pelusi, Rajendran Arunkumar and Ajay Nair
Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies o...
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Paulo Vitor de Campos Souza, Augusto Junio Guimarães, Thiago Silva Rezende, Vinicius Jonathan Silva Araujo and Vanessa Souza Araujo
The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern classification, including the detection of failures and anomalous behaviors. This paper discusses the use of an artificial intelligence model based on the ass...
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Ann Nosseir,Yahia Fathy
Pág. pp. 4 - 18
Identifying students at risk or potentials excellent students is increasingly important for higher education institutions to meet the needs of the students and develop efficient learning strategy. Early stage prediction can give an indication of the stud...
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Chidentree Treesatayapun
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer unit. W...
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Konstantinos I. Papageorgiou, Katarzyna Poczeta, Elpiniki Papageorgiou, Vassilis C. Gerogiannis and George Stamoulis
This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim of time series forecasting is to ...
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?????? ?????????? ???????, ??????? ????????????? ??????????
Pág. 42 - 49
The subject matter of the study is data clustering based on the ensemble of neural networks. The goal of the work is to create a new approach to solving the tasks of clustering in data streams when information is fed observation-by-observation in online ...
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Fernando Gaxiola, Patricia Melin, Fevrier Valdez, Oscar Castillo and Juan R. Castro
A comparison of different T-norms and S-norms for interval type-2 fuzzy number weights is proposed in this work. The interval type-2 fuzzy number weights are used in a neural network with an interval backpropagation learning enhanced method for weight ad...
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Usman T. Khan, Caterina Valeo
Pág. 1 - 24
A fuzzy neural network method is proposed to predict minimum daily dissolved oxygen concentration in the Bow River, in Calgary, Canada. Owing to the highly complex and uncertain physical system, a data-driven and fuzzy number based approach is preferred ...
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Olha Salnikova,Olga Cherviakova,Oleg Sova,Ruslan Zhyvotovskyi,Serhii Petruk,Taras Hurskyi,Andrii Shyshatskyi,Andrey Nos,Yevhenii Neroznak,Ihor Proshchyn
Pág. 35 - 44
Nowadays, artificial intelligence has entered into all spheres of human activity. However, there are some problems in the analysis of objects, for example, there is a priori uncertainty about the state of objects and the analysis takes place in a difficu...
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Cheng-Jian Lin, Chun-Hui Lin and Frank Lin
The spindle of a machine tool plays a key role in machining because the wear of a spindle might result in inaccurate production and decreased productivity. To understand the condition of a machine tool, a vector-based convolutional fuzzy neural network (...
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Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Nikolaos Papathanasiou, Dimitrios Apostolopoulos and Nikolaos Papandrianos
Myocardial Perfusion Imaging (MPI) has played a central role in the non-invasive identification of patients with Coronary Artery Disease (CAD). Clinical factors, such as recurrent diseases, predisposing factors, and diagnostic tests, also play a vital ro...
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Betty Saridou, Isidoros Moulas, Stavros Shiaeles and Basil Papadopoulos
Image conversion of malicious binaries, or binary visualisation, is a relevant approach in the security community. Recently, it has exceeded the role of a single-file malware analysis tool and has become a part of Intrusion Detection Systems (IDSs) thank...
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Salaheddin Hosseinzadeh, Hadi Larijani, Krystyna Curtis and Andrew Wixted
This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the tra...
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Paulo Vitor de Campos Souza, Augusto Junio Guimaraes, Vanessa Souza Araújo, Thiago Silva Rezende, Vinicius Jonathan Silva Araújo
Pág. 114 - 133
This paper presents a novel learning algorithm for fuzzy logic neuron based on neural networks and fuzzy systems able to generate accurate and transparent models. The learning algorithm is based on ideas from Extreme Learning Machine [36], to achieve a l...
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