Energy efficient communication is a plenary issue in Wireless Sensor Networks (WSNs). Contemporary energy efficient optimization schemes are focused on reducing power consumption in various aspects of hardware design, data processing, network protocols and operating system. In this paper, optimization of network is formulated by Cuckoo Based Particle Approach (CBPA). Nodes are deployed randomly...

Pattern synthesis is one of the most important aspects in antenna design. Arrays are more flexible to produce desired radiation characteristics. Difference patterns are usually generated with conventional techniques and there is less control on side lobes. In view of this, optimization techniques are applied to synthesize and produce such patterns optimally. The simulated patterns are produced ...

Data classification is one of the major tasks in data mining that organizes data in the proper manner to provide enhanced functionality to extract useful information from that data. There are various supervised and unsupervised machine learning techniques like FNN (Fuzzy Neural Network) presented by the researchers to provide an enhanced classification of the dataset. But the performance of the...

RNNs have local feedback loops within the network which allows them to shop earlier accessible patterns. This network can be educated with gradient descent back propagation and optimization technique such as second-order methods; conjugate gradient, quasi-Newton, Levenberg-Marquardt have also been used for networks training [14, 15]. But still this algorithm is not definite to find the global m...

Abstract Capacity prediction of surface mount production lines is important for improving productivity, dynamic scheduling, and optimizing structure. An integrated mutual information-cuckoo search-extreme learning machine (MI-CS-ELM) model proposed the impact nonlinear high-dimensional features surface-mounted on capacity. Firstly, affecting capacity are ranked based information method, predict...