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开发环境:Matlab
简要说明:动量-自适应学习调整算法。在实际应用中，原始的BP算法很难胜任，因此出现了很多的改进算法。BP算法的改进主要有两种途径，一种是采用启发式学习方法，另一种则是采用更有效的优化算法。本例采用动量BP算法，来实现对网络的训练过程，动量法降低了网络对于误差曲面局部细节的敏感性，有效地抑制网络陷于局部极小。-development environment : Matlab Brief Descr iption : Momentum-adaptive learning
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爬山算法是一种局部择优的方法，采用启发式方法，是对深度优先搜索的一种改进，它利用反馈信息帮助生成解的决策。 属于人工智能算法的一种。-Climbing algorithm is a partial merit-based approach, using heuristic methods, is a depth-first search of an improvement, which uses feedback information to generate solutions to help
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基于学习的深度优先搜索算法，一种通用的启发式搜索算法用于确定的，非确定以及MDPs环境中-Learning Depth-First Search:A Unified Approach to Heuristic Search in Deterministic and Non-Deterministic Settings,and its application to MDPs
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根据汽车内饰等行业需求,对皮制品加工的优化排样问题进行了研究.创新地采用离散化处理方式,同时引进边界约束,使排样过程与皮料和样片的几何信息无关,使用基于顺序的启发式底左布局将样片顺次布置到皮料上-According to the demand for such industries as automotive interior trim, leather processing for optimal layout problem is studied. Innovative approach o
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The paper is about bounds for LDPC and LDGM codes under MAP. A new method for analyzing low density parity check (LDPC) codes and low density generator
matrix (LDGM) codes under bit maximum a posteriori probability (MAP) decoding is
introduced. T
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Simulated Annealing (SA) is a smart (meta)-heuristic for Optimization. Given a cost function in a large search space, SA replaces the current solution by a random "nearby" solution. The nearby solution is chosen with a probability that depends on the
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Abstract. In this paper, we propose a method of hiding sensitive classification
rules from data mining algorithms for categorical datasets. Our
approach is to reconstruct a dataset according to the classification rules
that have been checked an
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关于DFT的文章，应用FPGA实现傅立叶变换。-Abstract—We present a domain-specific approach to generate
high-performance hardware-software partitioned implementations
of the discrete Fourier transform (DFT). The partitioning
strategy is a heuristic based on the DFT
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地面探测器发现海杂波中的目标一种方法 并有仿真-Based upon observations from real radar data measurements, a
heuristic approach exploiting a salient aspect of the idealized LRT
is developed which is shown to perform well when applied to real
measured sea clutter
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蚁群算法(ant colony algorithm，简称ACA)是20世纪90年代由意大利学者M．Dorigo等人首先提出来的一种新型的模拟进化算法．它的出现为解决NP一难问题提供了一条新的途径．用蚁群算法求解旅行商问题(TSP)、分配问题(QAP)、调度问题(JSP)等，取得了一系列较好的实验结果．虽然对蚁群算法研究的时间不长，但是初步研究已显示出蚁群算法在求解复杂优化问题(特别是离散优化问题)方面具有一定的优势，表明它是一种很有发展前景的方法．蚁群算法的主要特点是：正反馈、分布式计算．正反馈
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clips最新版
CLIPS是一种专家系统工具，最初由NASA/Lyndon B. Johnson太空中心软件技术研究室开发出来。自1986年首次发布以来，CLIPS经历了不断的改进和完善。现在它已经被广泛的应用在数以万计的全球用户中。 CLIPS被开发出来以促进集成人类知识和经验的软件发展。 在CLIPS中，知识的表示有三种方式： l 规则，规则表示法是基于启发式经验知识库的首要选择。 l 自定义函数和通用函数，这种方式是程序式知识表示的首选。 l 面向对象设计，也
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IEEE文章，启发式搜索策略用于
确定最佳的电容布局和
供配电系统的评等。在启发式
方法提出了一个关键的少数
名为“敏感节点，节点，选择
安装电容器优化净储蓄
同时实现了大的整体亏损减少。
这种方法保证了电压约束
会见。这种启发式的方法是适合大
配电系统，并可以在网上有用
实施。该方法是
用于测试系统和结果
与其他已发表的技术。
-Heuristic search strategies are used to
determine the o
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KMEAN C#
In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data sp
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In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Vo
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he increasing demand of networks, over the past decade has
led to the need for enormous cost reduction and increasing
accessibility of networks. It requires for efficient traffic management in the network and ability to expand as per the need.
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reconfiguration networks
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reconfiguration network
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Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages
finding the true global minimum regardless of the initial parameter values, fast convergence, and using
few control parameters
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Spoil names of symbols with C linkage, so use an heuristic approach to check if the name should be demangled.
-Spoil names of symbols with C linkage, so use an heuristic approach to check if the name should be demangled.
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OCCH RANDOMNESS (Optimised Connected Coverage Heuristic) approach Algorithm for WIreless Sensor Networks in Matlab
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