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With the rapid development of cloud computing services. The number of containers in the container cloud platform is increasing rapidly, but the resource allocation response speed of the server is slow, and the resource scheduling is unreasonable. To ...

The prediction of surface settlement occupies a crucial role in achieving effective catastrophe prevention and mitigation, as well as facilitating the maintenance of airport runways. Given the challenges associated with the manual collection of ...

Fractional gradient computation is a challenging task for neural networks. In this study, the brief history of fractional derivation is abstracted, and the core framework of the Faà di Bruno formula is implemented to the fractional gradient ...

• An analytical definition of fractional neural network theory is provided.
• Summurized historical evolution using nomenclature with update equations.
• Utilizing FNNs shows the enhancement of NN performance through fractional gradient.

Machine learning has shown great impact in a lot of applications. Within all types of tools, deep learning should be one of the most important techniques thanks to its ability to capture the correlation between the input features and output ...

• A more flexible HCF neuron model for DNNs is introduced; it constructs geometries in an n-dimensional space by changing weights and hyper-parameters and thus,...

Recent advances in deep neural networks (DNNs) have mainly focused on innovations in network architecture and loss function. In this paper, we introduce a flexible high-order coverage function (HCF) neuron model to replace the fully-...

This work focuses on cognitive users and its utilization of spectrum with channel bonding. Recurrent Channel Bonding Cognitive Users protocol (RCBCU) has been proposed. Spectrum access is enabled to cognitive users in the absence of primary users. ...

In mammography, the most frequently type of breast cancer recognized is DCISand the most frequent signs of DCIS are MCCs. In the proposed research work, MCs are enhanced using fuzzy approach. In this approach Gaussian fuzzy membership function is ...

Breast cancer is one of the primary causes of death that is occurred in females around the world. So, the recognition and categorization of initial phase breast cancer are necessary to help the patients to have suitable action. However, ...

Abnormal activity in the human brain is a symptom of epilepsy. Electroencephalogram (EEG) is a standard tool that has been widely used to detect seizures. A number of automated seizure detection systems based on EEG signal classification have been ...

We show that there are infinitely many valid scaled gradients which can be used to train a neural network. A novel training method is proposed that finds the best scaled gradients in each training iteration. The method’s implementation uses first ...

Representing the knowledge learned by neural networks in the form of interpretable rules is a prudent technique to justify the decisions made by neural networks. Heretofore many algorithms exist to extract symbolic rules from neural networks, but ...

Different industries were transitioning to the utilization of Industry 4.0 tools such as Artificial Intelligence (AI) techniques particularly Neural Network Modelling. The neural network application in pavement management is a serviceable tool to ...

With the rapid development and wide application of artificial neural networks, formal modeling and verification of their security become more and more significant. As a basic step towards the direction, this work proposes a comprehensive modeling ...

Nowadays Machine Learning approaches are getting popular in almost all the domains of Engineering Applications. One such widely used approach is Artificial Neural Networks (ANN), that has been successfully applied in many disciplines ...

• Detailed survey of shallow and deep ANNs in reservoir characterisation from 1993 to 2018.

To maintain a trade-off between robustness and imperceptibility, as well as secure transmission of digital images over communication channels, a digital image blind watermarking scheme on the basis of adaptive neuro-fuzzy inference system (ANFIS) ...

Nowadays, investigating new techniques to accelerate nonlinear systems’ simulations is a need because of their regular usage in industry. Systems’ simulators need to solve an enormous number of nonlinear equations. Software-based ...

Convolutional neural networks (CNNs) are one of the deep learning architectures capable of learning complex set of nonlinear features useful for effectively representing the structure of input to the network. Existing CNN architectures are invariant to ...

• VTCI is a near real-time indicator for drought monitoring and highly related to crop growth conditions.

Crop water stress and vegetation status are critical parameters and should be proposed as input variables of an integrated model for crop productivity and yield estimation. In this study, to improve the monitoring of the regional maize ...

The rapid development of social media services has spawned abundant user generated contents (UGC), such as Sina Weibo, which is one of the biggest Chinese microblogging platforms. In order to enhance the quality and popularity of the posted weibo ...

Tomography is a method to reconstruct the image of internal structure of some objects using signals or electromagnetic (EM) waves which are illuminated from several angles. In this paper, microwave tomography is proposed to reconstruct an internal ...