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- And then it researches the key techniques of data mining system in detail , including data preprocess , algorithm management , building algorithm library and data mining model visualization
然后詳細(xì)研究了構(gòu)建數(shù)據(jù)挖掘系統(tǒng)的關(guān)鍵技術(shù),包括數(shù)據(jù)的預(yù)處理、挖掘算法的管理、算法庫(kù)的構(gòu)建以及數(shù)據(jù)挖掘模型的可視化。 - On the base of the visual channel model library and estimation algorithm library , the paper advances a integrative design scheme of radio channel simulation environment , which has some technical innovation and practical value
本文在構(gòu)建可視化信道仿真模型庫(kù)和信道估計(jì)算法模型庫(kù)的基礎(chǔ)上，提出了一種集成化的無(wú)線信道仿真環(huán)境設(shè)計(jì)方案。 - It can integrate with existing operating system and can mine the data in distributed database . because of using the web services , it can be independent of platform and programming language , ease to be deployed and to manage algorithms library flexibly
它能夠與原有操作型系統(tǒng)良好集成,能夠挖掘分布式數(shù)據(jù)庫(kù)中的數(shù)據(jù),而且具有跨平臺(tái)、跨語(yǔ)言、易于部署和可動(dòng)態(tài)管理算法庫(kù)等優(yōu)點(diǎn)。 - The software system of dynamic balancing is based on dot ( object - oriented technology ) and com ( component object model ) was constructed by the first - rate software development kit ? visual c + + 6 . 0 and the efficient algorithms library matlab c + + math library
本文利用優(yōu)秀的軟件開發(fā)平臺(tái)visualc + + 6 . 0和具備高效算法的matlabc + +數(shù)學(xué)庫(kù)，采用面向?qū)ο蠛突诮M件的高級(jí)軟件技術(shù)開發(fā)了一個(gè)基于個(gè)人計(jì)算機(jī)的動(dòng)平衡軟件系統(tǒng)。 - Bringing forward an intelligent decision method of image segmentation based on roughset theory to make the system automatically select segmentation algorithm in simple scenes . firstly , it selects some representative segmentation algorithms to make up of an algorithm library , which is used to process kinds of sample images ; secondly , it makes the decision informationtable utilizing diversified numerical features extracted from the sample images and the optimalsegmentation algorithm of each sample image according to segmentation quality evaluationcriterion ; finally , it applies rough set theory on discretization and attribution reduction of
為了使系統(tǒng)在簡(jiǎn)單場(chǎng)景下能夠通過(guò)自動(dòng)選取分割算法來(lái)提取目標(biāo),提出了一種基于粗糙集理論的圖像分割智能決策方法。首先選取若干具代表性的分割算法構(gòu)成算法庫(kù),并用它們對(duì)各種樣本圖像進(jìn)行分割;然后利用從樣本圖像中提取出來(lái)的各種數(shù)值特征,并根據(jù)圖像分割質(zhì)量評(píng)價(jià)標(biāo)準(zhǔn)評(píng)判出各樣本圖像的最優(yōu)分割算法,用其構(gòu)成決策信息表;最后應(yīng)用粗糙集理論來(lái)對(duì)決策信息表進(jìn)行離散化處理和屬性約簡(jiǎn),以生成圖像分割算法選取的決策規(guī)則。