Remote sensing images classification method can be divided into supervised classification and unsupervised classification according to whether there is prior knowledge. Supervised classification is a machine learning ...
详细信息
ISBN:
(纸本)9783642173158
Remote sensing images classification method can be divided into supervised classification and unsupervised classification according to whether there is prior knowledge. Supervised classification is a machine learning procedure for deducing a function from training data;unsupervised classification is a kind of classification which no training sample is available and subdivision of the feature space is achieved by identifying natural groupings present in the images values. As a branch of swarm intelligence, ant colony optimization algorithm has self-organization, adaptation, positive feedback and other intelligent advantages. In this paper, ant colony optimization algorithm is tentatively introduced into unsupervised classification of remote sensing images. A series of experiments are performed with remote sensing data. Comparing with the K-mean and the ISODATA clustering algorithm, the experiment result proves that artificial ant colony optimization algorithm provides a more effective approach to remote sensing images classification.
Given a connected edge-weighted undirected graph, the min-degree constrained minimum spanning tree (MDCMST) problem seeks on this graph a spanning tree of least cost in which every non-leaf node have a degree of at le...
详细信息
ISBN:
(纸本)9783319037554;9783319037561
Given a connected edge-weighted undirected graph, the min-degree constrained minimum spanning tree (MDCMST) problem seeks on this graph a spanning tree of least cost in which every non-leaf node have a degree of at least d in the spanning tree. This problem is NP-Hard for 3 <= d <= left perpendicularn/2right perpendicular where n is the number of nodes in the graph. In this paper, we have proposed an antcolonyoptimization based approach to this problem. The proposed approach has been tested on Euclidean and random instances both. Computational results show the effectiveness of the proposed approach.
A serious emerging games engine (SEGE) must make explicit the possibility of emergence in a serious game (SG), from the coordinated handling of game plot, adapted to the specific educational context where it is being ...
详细信息
ISBN:
(纸本)9781728155746
A serious emerging games engine (SEGE) must make explicit the possibility of emergence in a serious game (SG), from the coordinated handling of game plot, adapted to the specific educational context where it is being developed. In previous articles a SEGE based on the ant colony optimization algorithm (ACO) has been proposed, which allows the initial emergence of a SG. In the present work the adaptive plot system (APS) is specified, which allows the emergence of plot in a serious game emerging (SGE), and is based on an ACO that changes the plot in the game, according to the theme that is being given in a smart classroom SaCI (Salon de Clase Inteligente, for its acronym in Spanish),). The APS performs the management of a set of game plot that may be of interest in a context-educational domain, in such a way to adapt the SGE initially conceived to the subject taught in the SaCI, in order to make the appropriate SGE emerge Pedagogical process in progress. Additionally, this paper analyzes the behavior of APS in a case study, showing very encouraging results as SEGE.
To reduce the assembly efforts and cost of the assembly, researchers are motivated to reduce the part number by applying design for assembly (DFA) concept. The so far existed literature review has no generalized metho...
详细信息
ISBN:
(纸本)9789811080555;9789811080548
To reduce the assembly efforts and cost of the assembly, researchers are motivated to reduce the part number by applying design for assembly (DFA) concept. The so far existed literature review has no generalized method to obtain optimum assembly sequence by incorporating the DFA concept. Even though the DFA concept is applied separately, still it demands high-skilled user intervention to obtain optimum assembly sequence. As the assembly sequence planning (ASP) is NP-hard and multi-objective optimization problem, it requires more computational time and huge search space. In this paper, an attempt is made to combine DFA concept along with ASP problem to obtain optimum assembly sequence. ant colony optimization algorithm (ACO) is used for combining DFA and ASP problem by considering directional changes as fitness function to obtain optimum feasible assembly sequences. Generally, the product with 'N' parts consists of N - 1 levels during assembly, which are reduced by applying DFA concept. Later on, optimum assembly sequence can be obtained for the reduced levels of assembly using different assembly predicates.
Feature selection and feature extraction are the most important steps in classification problems. Feature selection is commonly used to reduce dimensionality of datasets with tens or hundreds of thousands of features ...
详细信息
ISBN:
(纸本)9783642352690
Feature selection and feature extraction are the most important steps in classification problems. Feature selection is commonly used to reduce dimensionality of datasets with tens or hundreds of thousands of features which would be impossible to process further. One of the problems in which feature selection is essential is content-based image classification problems. This paper presents a novel method for image classification method based on an ant colony optimization algorithm which can significantly improve the classification performance for content-based image retrieval in cloud computing environment. ant colony optimization algorithm is inspired by observation on real ants in their search for the shortest paths to food sources. The proposed algorithm is easily implemented and because of use of a simple classifier in that, its computational complexity is very low. We compared the previous algorithm with the proposed algorithm in terms of image classification performance. As a result, the proposed algorithm showed higher performance in terms of accuracy.
The ant colony optimization algorithm has been widely studied and many important results have been *** this algorithm has been applied to many fields,the analysis about its convergence is much less,which will influenc...
详细信息
The ant colony optimization algorithm has been widely studied and many important results have been *** this algorithm has been applied to many fields,the analysis about its convergence is much less,which will influence the improvement of this ***,the convergence of this algorithm applied to the traveling salesman problem(TSP)was analyzed in *** conclusion that this algorithm will definitely converge to the optimal solution under the condition of 0
Route planning for transmission lines has always been an important part of the power construction industry. In the past, however, such planning has involved many critical steps, not only collecting complex geographic ...
详细信息
This paper develops a novel path planning algorithm using improved antcolonyoptimization (ACO) and its FPGA implementation. The proposed approach can effectively increase the accuracy to generate an optimal path. Th...
详细信息
ISBN:
(纸本)9781479987481
This paper develops a novel path planning algorithm using improved antcolonyoptimization (ACO) and its FPGA implementation. The proposed approach can effectively increase the accuracy to generate an optimal path. The main idea of this paper is to avoid local minimum by continuous tuning of a setting parameter and the establishment of new mechanisms for opposite pheromone updating and partial pheromone updating. Experimental results show that the execution efficiency of path planning is significantly improved by full hardware design for embedded applications.
This study aim is to design a road anomaly transmission algorithms using antcolonyoptimization (ACO) based Technique in a Vehicle-to-Vehicle (V2V) and Vehicle to Infrastructure (V2I) Communication. The developed VAC...
详细信息
ISBN:
(纸本)9781728151601
This study aim is to design a road anomaly transmission algorithms using antcolonyoptimization (ACO) based Technique in a Vehicle-to-Vehicle (V2V) and Vehicle to Infrastructure (V2I) Communication. The developed VACO also uses the features of VANET to find out the optimal path by considering a minimum number of nodes and cost parameters, which provides information related to accidents, speed of neighbouring vehicle and weather to help users in making informed decisions. Vehicle routing protocol based on ACO (VACO) also ensures to mitigate issues by combining the reactive and proactive approach and considers the parameters affecting the Quality of Service (QoS) such as latency, bandwidth, and delivery ratio in evaluating the algorithms.
作者：
Liu, HongLi, PingWen, YuZhejiang Univ
Natl Lab Ind Control Technol Res Ctr Intelligent Transportat Syst Hangzhou 310027 Zhejiang Provin Peoples R China
ant colony optimization algorithm is a good way to solve complex multi-stage decision problems. But the construction graph and computation steps for an ant to construct a solution in the construction graph will be exp...
详细信息
ISBN:
(纸本)1424403316
ant colony optimization algorithm is a good way to solve complex multi-stage decision problems. But the construction graph and computation steps for an ant to construct a solution in the construction graph will be exponentially increased, if the stage number and decision variable dimension of complex multi-stage decision problem are increasing. It will cause the ant colony optimization algorithm can not be computed by a single PC. Therefore, a parallel ant colony optimization algorithm based on the construction graph decomposition is presented to solve this problem. The parallel ant colony optimization algorithm decomposes the construction graph into some parts and each part is placed on different PC. The whole computation task is accomplished by mutual cooperation in the PCs which join in the computation. Experiment has verified that it can solve this problem and improve the computation efficiency.
暂无评论