In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)

This research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri

In this paper, we characterize the percolation condition for a continuum secondary cognitive radio network under the SINR model. We show that the well-established condition for continuum percolation does not hold true in the SINR regime. Thus, we find the condition under which a cognitive radio network percolates. We argue that due to the SINR requirements of the secondaries along with the interference tolerance of the primaries, not all the deployed secondary nodes necessarily contribute towards the percolation process- even though they might participate in the communication process. We model the invisibility of such nodes using the concept of Poisson thinning, both in the presence and absence of primaries. Invisibility occurs due to nodes

The physical and morphological characteristics of porous silicon (PS) synthesized via gas sensor was assessed by electrochemical etching for a Si wafer in diluted HF acid in water (1:4) at different etching times and different currents. The morphology for PS wafers by AFM show that the average pore diameter varies from 48.63 to 72.54 nm with increasing etching time from 5 to 15min and from 72.54 to 51.37nm with increasing current from 10 to 30 mA. From the study, it was found that the gas sensitivity of In2O3: CdO semiconductor, against NO2 gas, directly correlated to the nanoparticles size, and its sensitivity increases with increasing operating temperature.