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Accurate prediction of solar activity as one aspect of space weather phenomena is essential to decrease the damage from these activities on the ground based communication, power grids, etc. Recently, the connectionist models of the brain such as neural networks and neuro-fuzzy methods have been proposed to forecast space weather phenomena; however, they have not been able to predict solar activity...
A military training radio network requires support for a large number of mobile nodes with heterogeneous traffic and real-time requirements. We propose a deterministic protocol and an admission control using real-time analysis for a centralized radio network with a multichannel base station. The admission control implements an algorithm for frequency allocation to mobile nodes, and guarantees timely...
Military training radio networks typically consist of large numbers of mobile nodes and have to provide real-time (RT) communication between these nodes. This paper introduces a method on how to manage radio resources and provide Quality of Service (QoS) guarantees for heterogeneous traffic by using admission control, deterministic queuing, and scheduling methods. The proposed solution is based on...
This paper introduces a new type of brain emotional learning inspired models (BELIMs). The suggested model is utilized as a suitable model for predicting geomagnetic storms. The model is known as BELPM which is an acronym for Brain Emotional Learning-based Prediction Model. The structure of the suggested model consists of four main parts and mimics the corresponding regions of the neural structure...
This study presents comparative results obtained from employing four different neuro-fuzzy models to predict geomagnetic storms. Two of thes neuro-fuzzy models can be classified as Brain Emotional Learning Inspired Models (BELIMs) These two models are BELFIS (Brain Emotional Learning Based Fuzzy Inference System) and BELRFS (Brain Emotional Learning Recurrent Fuzzy System). The two other models are...
This paper presents the results of applying a new clustering algorithm in ad hoc networks. This algorithm is a centralized method and is designed on the basis of an imperialist competitive algorithm (ICA). This algorithm aims to find a minimum number of cluster-heads while satisfying two constraints, the connectivity and interference. This work is a part of an ongoing research to develop a distributed...
This paper presents a modified model of brain emotional learning based fuzzy inference system (BELFIS). It has been suggested to predict chaotic time series. We modify the BELFIS model merging radial basis function network with adaptive neuro-fuzzy network. The suggested model is evaluated by testing on complex systems and the obtained results are compared with the results of other studies.
There will always be a security gap between our ability to secure our networks and the actual level of security needed. When securing our networks we need good intelligence to direct our efforts and focus on the right spots. We need to find those spots and they can be found, with the right tools. Survival time is a method that provides possibilities to make decisions concerning information security...
In this paper, we suggest an inspired architecture by brain emotional processing for classification applications. The architecture is a type of ensemble classifier and is referred to as ‘emotional learning-inspired ensemble classifier’ (ELiEC). In this paper, we suggest the weighted k-nearest neighbor classifier as the basic classifier of ELiEC. We evaluate the ELiEC's performance by classifying some...
This paper presents new channel assignment algorithm for a clustered ad hoc network. The suggested method is based on a graph-theoretic model and seeks a solution for the channel assignment problem in a clustered ad hoc network. The method is based on a new meta-heuristic algorithm that is referred to as imperialist competitive algorithm (ICA). It provides a scheme for allocating the available channels...
This paper presents a new architecture based on a brain emotional learning model that can be used in a wide varieties of AI applications such as prediction, identification and classification. The architecture is referred to as: Brain Emotional Learning Based Fuzzy Inference System (BELFIS) and it is developed from merging the idea of prior emotional models with fuzzy inference systems. The main aim...
In this paper a novel optimization method called imperialist competitive algorithm (ICA) is applied to solve the channel assignment problem in a mobile ad hoc network. First the imperialist competitive algorithm (ICA) is described, which has been proposed as an evolutionary optimization method, and after that it is explained how it can seek a near optimal solution for the channel allocation problem...
This paper suggests a novel learning model for prediction of chaotic time series, brain emotional learning-based recurrent fuzzy system (BELRFS). The prediction model is inspired by the emotional learning system of the mammal brain. BELRFS is applied for predicting Lorenz and Ikeda time series and the results are compared with the results from a prediction model based on local linear neuro-fuzzy models...
Industrial communication often has to work in an environment where other networks or radiation create different levels of interference for the data traffic. Additionally, industrial applications often demand predictable real-time performance of the network. One way of trying to utilise the available frequencies in an effective manner is to include cognitive functionality in the network. We present...
A novel radio receiver circuit, functioning as a tuned active, detecting antenna, is described. The receiver is suggested to be part of a new radio system with the potential of competing with the range capability of active RFID-tags and, through its low power and long lifetime, with passive RFID-tags. The circuit is outlined and the functionality is verified by simulations and measurements. A 24 MHz...
In this paper we present a novel active radio frequency identification system consisting of transponders with low complexity, low power consumption, and long system reading range. The transponder's low complexity and small circuit integration area indicate that the production cost is comparable to the one of a passive tag. The hardware keystone is the transponder's radio wake-up transceiver, which...
This paper suggests a cluster collision avoidance mechanism and a dual transceiver architecture to be used in a clustered wireless multihop network. These two contributions make the clustered wireless multihop network the preferred architecture for future industrial wireless networks. The wireless multihop cluster consists of one master and several slaves, where some of the slaves will act as gateways...
Traffic safety applications using vehicle-to-vehicle (V2V) communication is an emerging and promising area within the intelligent transportation systems (ITS) sphere. Many of these new applications require real-time communication with high reliability, meaning that packets must be successfully delivered before a certain deadline. Applications with early deadlines are expected to require direct V2V...
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