swarm system 2019


Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence.

Deep reinforcement learning for swarm systems
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Recently, deep reinforcement learning (RL) methods have been applied successfully to multi-agent scenarios. Typically, the observation vector for decentralized decision making is represented by a concatenation of the (local) information an agent gathers about other

Random walk exploration for swarm mapping
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Research in swarm robotics has shown that robot swarms are effective in the exploration of unknown environments. However, little work has been devoted to port the exploration capabilities of robot swarms into the context of mapping. Indeed, conceiving robot swarms

A review of techniques for online control of parameters in swarm intelligence and evolutionary computation algorithms
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The two major groups representing biologically inspired algorithms are Swarm Intelligence (SI) and Evolutionary Computation (EC). Both SI and EC share common features such as the use of stochastic components during the optimization process and various parameters for

Adaptive exploration of a UAVs swarm for distributed targets detection and tracking
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This paper focuses on the problem of coordinating multiple UAVs for distributed targets detection and tracking, in different technological and environmental settings. The proposed approach is founded on the concept of swarm behavior in multi-agent systems, ie, a self

Particle Swarm Optimization based Fuzzy Logic MPPT Inverter Controller for Grid Connected Wind Turbine
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The wind energy source as an alternative to conventional sources to generate power has been increasingly popular due to abundant in nature and pollution free. The wind energy sources are undepletable, however, they are not able to generate as much electricity due to

A modified comprehensive learning particle swarm optimizer and its application in cylindricity error evaluation problem
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Particle swarm optimizer was proposed in 1995, and since then, it has become an extremely popular swarm intelligent algorithm with widespread applications. Many modified versions of it have been developed, in which, comprehensive learning particle swarm optimizer is a very

Particle swarm optimization for the estimation of surface complexation constants with the geochemical model PHREEQC-3.1. 2
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Sorption of metals on minerals is a key process in treatment water, natural aquatic environments, and other water-related technologies. Sorption processes are usually simulated with surface complexation models; however, identifying numeric values for the

A SWARM -BASED META-HEURISTIC FOR RELAY NODES PLACEMENT IN WIRELESS SENSOR NETWORKS
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A Wireless Sensor Network (WSN) is a network consisting of wireless sensor nodes. There are usually requirements that need to be met when deploying a WSN, one being the placement of nodes. Due to placement requirements and limited node transmission range, a

A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation
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With the increasing global demands for energy, fuel supply management is a challenging task of todayLs industries in order to decrease the cost of energy and diminish its adverse environmental impacts. To have a more environmentally friendly fuel supply network

Distributed Generation in a Distribution Network in Presence of Renewable and Load Uncertainties by Mixed Discrete Particle Swarm Based Point Estimate
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This paper presents the uncertainty analysis of a Distribution Network (DNR) caused by Unit Power Output Control (UPC) DGs (Solar, Wind) and load demand by point estimate method (PEM) based on Mixed Discrete PSO (MDPSO) technique. The uncertainties are taken care

OPTIMIZATION AND SIMULATION OF JOB-SHOP SUPPLY CHAIN SCHEDULING IN MANUFACTURING ENTERPRISES BASED ON PARTICLE SWARM
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The production scheduling of supply chain is the key to the improvement of production efficiency and resource utilization in manufacturing enterprise. For effective scheduling of job-shop production, this paper puts forward a scheduling optimization method for job-shop

Dual Heuristic Feature Selection Based on Genetic Algorithm and Binary Particle Swarm Optimization
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The features selection is one of the data mining tools that used to select the most important features of a given dataset. It contributes to save time and memory during the handling a given dataset. According to these principles, we have proposed features selection method

An Improved Unsupervised Image Segmentation Method Based on Multi-Objective Particle Swarm Optimization Clustering Algorithm
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Most image segmentation methods based on clustering algorithms use singleobjective function to implement image segmentation. To avoid the defect, this paper proposes a new image segmentation method based on a multi-objective particle swarm optimization (PSO)

Improved Particle Swarm Optimization for Selection of Shield Tunneling Parameter Values
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This article proposes an exponential adjustment inertia weight immune particle swarm optimization (EAIW-IPSO) to enhance the accuracy and reliability regarding the selection of shield tunneling parameter values. According to the iteration changes and the range of

SCHEDULING OPTIMIZATION OF CLOUD RESOURCE SUPPLY CHAIN THROUGH MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION.
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The cloud manufacturing, a new service-oriented manufacturing mode, has become a hotspot in manufacturing industry. Considering supply chain scheduling optimization as a multi-objective optimization problem, this paper combines the fuzzy correlation entropy

SAFETY PATH PLANNING WITH OBSTACLE AVOIDANCE USING PARTICLE SWARM OPTIMIZATION FOR AGV IN MANUFACTURING LAYOUT
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In robotic systems, path planning is the one of important processes for robot motion. The best path planning is required for shortest path searching that can make fast movement of robot. However, the real environment is not only the path from point to point but it has

Solving the planning and scheduling problem simultaneously in a hospital with a bi-layer discrete particle swarm optimization.
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The operating room is one of the most capital-intensive resources for a hospital. To achieve further improvements and to restrict cost increases, hospitals may need to operate more efficiently with the resources they already possess. The paper considers the joint problem of

Cost Optimization of No-Slump Concrete Using Genetic Algorithm and Particle Swarm Optimization
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(NSC) is investigated in this study. In this investigation, some restriction for the amount of compressive strength is considered and overall cost of concrete is minimized by designing mixture proportion. Cement, silica fume, water, fine aggregate, coarse aggregate and filler

A hybrid bacterial foraging and modified particle swarm optimization for model order reduction
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This paper study the model reduction procedures used for the reduction of large-scale dynamic models into a smaller one through some sort of differential and algebraic equations. A confirmed relevance between these two models exists, and it shows same



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