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Gravitational Search Algorithm (GSA) is a population-based optimization algorithm based on Newton's law of gravity and the notion of mass interactions. GSA has the advantage of proper global search ability. However, it suffers from weak local search due to relatively big step-size of agents in the search process. In order to improve the balance between exploration and exploitation of GSA, two mechanisms...
Communities are basic units of complex networks and understanding of their structure help us to understand the structure of a network. Communities are groups of nodes that have many links inside and few links outside them. Community detection in a network can be modeled as an optimization problem. We can use some measures such as Modularity and Community Score for evaluating the quality of a partition...
A complex product is generally a system composed of numerous interdependent components, each one representing specific disciplines and developed using associated expertise. When analysing the problem from another point of view, we can see that for each design domain, a generally huge set of real already designed elements exists. Thus, when constructing a new element, it is interesting to use this...
There are many factors affect the stability of reservoir slopes, each of them is associated and coupled with others. Generally, the analysis of slopes stability can be achieved by the method of effect-factors analogy and cluster analysis. Traditional cluster analysis is difficult to obtain the stable global optimal solution, since the results are sensitive to the initial cluster center and the order...
The goal of image segmentation is to cluster pixels into salient image regions, it is the most significant step in image analysis. Thresholding is a simple but effective tool to separate objects from the background, which is one of the most popular algorithms. The artificial bee colony algorithm (ABC) is a recently presented meta-heuristic algorithm, which has been successfully applied to solve many...
Many VMI Supply Chains produced a set of candidate stock addresses. The set was clustered by distance and storage. Only one address was selected to found warehouse in every class. The address is selected by all VMI supply chains which decides to found warehourse in that class. All VMI Supply Chains share the storage in one stock address class. Every VMI Supply Chain makes optimization of path itself...
The artificial bee colony algorithm is a swarm intelligence optimization algorithm inspired by the intelligent foraging behavior of honeybees. In this paper, modified ABC algorithms are proposed for numerical optimization. We have compared the performance of our ABC approach against the basic ABC algorithm, results show that the proposed methods have somewhat improved the convergence rate and global...
MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) algorithms on massive datasets has led to an increased interest in implementing ML algorithms on MapReduce. However, the cost of implementing a large class of ML algorithms as low-level MapReduce jobs on varying data and machine cluster...
The instruction cache is a critical component in any microprocessor. It must have high performance to enable fetching of instructions on every cycle. However, current designs waste a large amount of energy on each access as tags and data banks from all cache ways are consulted in parallel to fetch the correct instructions as quickly as possible. Existing approaches to reduce this overhead remove unnecessary...
Regardless of creation method, Fuzzy rules are of great importance in the implementation and optimization systems. Although using human knowledge in creating Fuzzy rules, has the advantage of readability and is near the experimental expertise, but it cannot be implemented in all systems. Since Output of a system is based on its correct function over the time, output data is reliable with higher percentage...
The k-core of a graph is the largest subgraph in which every vertex is connected to at least k other vertices within the subgraph. Core decomposition finds the k-core of the graph for every possible k. Past studies have shown important applications of core decomposition such as in the study of the properties of large networks (e.g., sustainability, connectivity, centrality, etc.), for solving NP-hard...
ZACA-EEC (Zigbee Ant Colony Algorithm Energy Efficient Cluster) routing protocol is proposed to replace AODV in Zigbee with the aim of increasing reliability for mine equipment monitoring in this paper, which can prolong the lifetime of network remarkably. Taking hydraulic support as an example, the distribution of monitoring nodes can be simplified as chain hierarchy topology, then Free-space model...
In order to make good use of the limited energy, ant colony optimization (ACO) was applied to inter-cluster routing mechanism. An uneven clustering routing algorithm for Wireless Sensor Networks (WSNs) based on ant colony optimization (ACO) was proposed. The algorithm utilized the dynamic adaptability and optimization capabilities of the ant colony to get the optimum route between the cluster head...
An algorithm based on ant colony algorithm for health condition monitoring of aero-engine was put forward. The algorithm conversed the health status classification of aero-engine into solving the clustering-based optimization problem with constrain. Ant colony algorithm based on colony collaboration and learning could solve this clustering problem. The proposed algorithm was applied to monitor health...
Adaptive data-driven dictionaries for sparse approximations provide superior performance compared to predefined dictionaries in applications involving representation and classification of data. In this paper, we propose a novel algorithm for learning global dictionaries particularly suited to the sparse representation of natural images. The proposed algorithm uses a hierarchical energy based learning...
The function and structure and the architecture of sensor network based on ZigBee/802.15.4 standard for forest monitoring are designed in this paper. According to the features of forest monitoring, the sensor nodes based on CC2520 and low power consumption chip MSP430F5437 and the coordinator Combing with ARM are designed which realize the energy control in physical layer. With the wireless sensor...
In many real-world applications, the accurate number of clusters in the data set may be unknown in advance. In addition, clustering criteria are usually high dimensional, nonlinear and multi-model functions and most existing clustering algorithms are only able to achieve a clustering solution that locally optimizes them. Therefore, a single clustering criterion sometimes fails to identify all clusters...
Spatial clustering is very relevant to its sample distribution, clustering geometry configuration and spatial structure. Hierarchy dividing of spatial clustering and its optimization has been studied based on K-means algorithm in this paper. It recommends a classical method of hierarchy dividing of spatial clustering and a new rule to optimize the k value of spatial clustering. The rule and its expansibility...
Robust biometric recognition is of paramount importance in security and surveillance applications. In face based biometric systems, data is usually collected using a video camera with high frame rate and thus the captured data has high redundancy. Selecting the appropriate instances from this data to update a classification model, is a significant, yet valuable challenge. Active learning methods have...
In this paper, an improved ant colony optimization based approach for image edge detection is proposed. The algorithm use ant colony clustering approach to extract edge feature. The approach set the heuristics information function and the initial cluster, thus avoiding the search blindness which carried out by traditional ant colony algorithm. And a series of simulation experiments demonstrate the...
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