Swarm intelligence

Swarm intelligence: Nature presents suggestion to the humans in many ways. One way of such inspiration is the best way in which ordinary organisms behave when they 're in groups. example a swarm of ants, a swarm of bees, a colony of microorganism, in these scenario and in many other, biologists have informed us that the workforce of group of individuals itself reveals behavior that the character individuals don 't, or cannot. In other phrases, if we recall the workforce itself as an individual or

Abstract— Swarm intelligence (SI) is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems. The project proposes a swarm intelligence-based procedure to detect critical conditions of a patient, affected by a specific disease, at an early stage in absence of clinician. The procedure is to be integrated

Swarm Intelligence: Concepts, Models and Applications Technical Report 2012-585 Hazem Ahmed Janice Glasgow School of Computing Queen 's University Kingston, Ontario, Canada K7L3N6 {hazem, janice}@cs.queensu.ca February 2012 Report Index 1. 2. Introduction ........................................................................................................................ 2 Swarm Intelligence (SI) Models ......................................................................

combinatorial optimization problem, Vehicle Routing Problem (VRP). The VRP has many variants. In this project we will keep focus on one such variant, Capacitated Vehicle Routing Problem (CVRP). Swarm Intelligence is a new emerging field for solving such combinatorial optimization problems. Swarm Intelligence, in particular, Ant Colony metaheuristic is inspired from the way ants search for food by building shortest path between food and nest. Our objective in this project is to develop and enhance Ant

For a project to be successfully completed before due dates and keeping budget under control optimum utilization of resources is necessary; however, these limits may sometimes surpass. A significant variance may be there between certain assumptions made during initial planning of project and final outcomes. Unforeseen and unknown changes in construction methods, materials, techniques, or human resources may create budgetary and scheduling pressures which may increase the possibility of failure (Zeng

AN EXTENSIVE RESEARCH ON MULTI ROBOT FOARGING USING SWARMS FOR E-WASTE COLLECTION 1. INTRODUCTION: Classical robots are usually single complex pieces of electromechanical hardware designed to perform a task. They are typically expensive, specialized, and complicated. An alternate approach is to use a swarm" composed of a large number of very simple robots that work together, rather than a single highly capable robot. In this approach, the strength of the system comes not from the complexity and power

inspired algorithms and to motivate the researchers. Keyword -Nature Inspired Algorithms, Evolutionary Algorithm, Stochastic global search algorithm , Swarm Intelligence, Bio-Inspired Algorithms. I. INTRODUCTION Nature has the ability to solve and optimize the complex problem by logical and effective ways. Nature has provided us the intelligence ,self learning , pattern recognition, optimization etc. The mostly followed nature-inspired models of computation are genetic algorithm, neural computation

many practical situations, considering the fact that security personnel should act quickly if something seems to be “unusual”. Anomalous is a problem which is not fitting into a familiar type, classification or pattern. HOS (Histogram of Oriented Swarm) is used for detecting and localizing anomalous events in videos of crowded scenes. HOS together with the HOG (Histogram of Oriented Gradient) are combined to give a descriptor that helps to effectively characterize each scene. The occurrences of gradient

In this section, we introduce the main contribution of this paper. We design a single database scan efficient method to mine various kinds of spatiotemporal swarms using four kinds of pruning methods which reduce the computational cost. Then, we discover some significant trajectory locations and strong relationships among the objects. The following subsections formalize the concepts and introduce a detailed description of the proposed method. \begin{figure}[htp] \centering \includegraphics[width=0

Many researchers have proposed various methodologies for finding best solution. J. Ross Quinlan. In machine learning community, the decision tree algorithms, Quinlan’s ID3 and its successor C4.5: Programs for machine learning are probably the most popular. The various issues related to decision tree are discussed from the initial state of building a tree to methods of pruning, converting trees into rules and handling other problems such as missing attribute values. Apart from that