machine learning system 中文意思是什麼
machine learning system
解釋
機器學習系統-
During the procedure of system design and implementation, the author has made some innovative efforts such as : ( d establishing the user interest orientated model, the model receiving user interests continuously and conjecturing user interests by interaction with the user, accumulating user preferences in information demand, thereby achieving self - adaptive retrieval, ? roviding a feedback method which is based on the human - machine interaction, summarizing the user operations on the interface of result presentation, and designing an algorithm for capturing user operation behaviors, by which the changes in user interests and preferences can be learned potentially, ? ffering a method for user interest mining which can extract subjects of information confirmed by user, thereby conjecturing or predicting different kinds of expressions of the same interest or extracting the new interests or unexpressed interests, ? roposing a solution of personalized internet information retrieval based on the user interests in accordance with the above - mentioned work, the solution having very strong feasibility and practicality with taking user interest model as center, employing machine learning ( active learning and passive learning ) and data mining as tools, and being assisted with network robot,
Piirs系統分析與設計過程中所做的創新性的嘗試主要有以下幾個方面：實現了基於用戶興趣的用戶模型，該模型通過與用戶的交互（主動交互和被動交互） ，不斷地接收用戶的興趣和推測用戶的興趣，積累用戶信息需求的偏好，實現自適應的檢索；提供了一種基於人機交互的反饋方法，對用戶在結果呈現界面上的操作進行了歸納總結，設計了用戶操作捕獲演算法， 「隱性地」學習用戶興趣和偏好的變化；提供了一種用戶需求挖掘的方法，對用戶已確定的信息做進一步的主題挖掘，由此推測或預測用戶同一興趣的不同表述方式或者挖掘出用戶新的或未表達出來的興趣；在上述工作基礎上提出了一套完整的基於用戶興趣的個性化網路信息檢索的解決方案，該方案以用戶興趣模型為中心，以機器學習（主動學習和被動學習）和數據挖掘為手段，輔以網路機器人，具有很強的可行性和實用性。 -
While network - based intrusion detection systems usually detect packet headers or part of those headers, this system examines the packet payload as well as headers. not only the attributes are detected respectively, but also the relationships of attributes occurrence are detected according to a set of conditional rules, which is generated automatically by a machine learning algorithm
常見的基於網路的入侵檢測系統一般只對網路數據包的包頭或包頭中的某些內容進行考察，而本文實現的原型系統不僅考察數據包的包頭，而且還考察數據包應用負載的部分內容。 -
2 ， a machine learning method for extracting go joseki for computer go system is proposed in this dissertation
2 ，通過機器學習的方法，從棋譜中自動獲取定式，建立定式庫。 -
In recent years, reinforcement learning has become one of the key research areas in artificial intelligence and machine learning and it has attracted many researchers in other fields including operations research, control theory and robotics. reinforcement learning is different from supervised learning in that no teacher signals are needed and a reinforcement learning system learns by interacting with the environment to maximize the evaluative feedback from the environment
增強學習與監督學習的不同之處在於，增強學習不要求給定各種狀態下的期望輸出即教師信號，而強調在與環境交互中的學習，以極大（或極小）化從環境獲得的評價性反饋信號為學習目標。 -
An experienced human operator may have little knowledge about a complex system but can still doing good job in system control and fault diagnosis by observing signals of inputs and outputs. therefore, the problem is, can we use some techniques of machine learning and artificial intelligent to mimic the human ability of " learn to control "
在實際工業生產中，工程技術人員在對系統機理和數學模型知之甚少的情況下通過觀察和經驗總結，仍然能夠對系統進行良好的手動控制和及時的故障診斷，因此完全可以採用機器學習的智能方法模擬人的這種通過觀察學習進行控制的能力。 -
Firstly, the backgrounds and techniques of intrusion detection system ( ids ) are introduced briefly in this paper, also the current status. then an intrusion detection system based on a new nonstationary machine learning technique model is presented and improved. on the precondition of the same false alarm rates, more intrusions have been detected, and less time for detection is needed with the improved system
本文首先引入了一種基於機器學習規則的、用於入侵檢測系統的動態模型，並對該模型加以改進，在誤警率不變的前提下，使系統能夠檢測到更多的入侵種類，縮短了系統檢測時間，從而提高了系統性能。 -
The main work at the beginning of 1970 ' s was to construct the machine learning system that can simulate human ' s concept acquision
第二階段是20世紀70年代初。主要工作是建立各種模擬人的概念學習的機器學習系統。 -
Failure diagnosis expert system for pressure vessels is made up of knowledge base, knowledge base management system, inference machine, integrated database, self learning system, explanation machine and human - machine interface etc. knowledge base and inference machine are absolutely necessary
壓力容器失效分析專家系統由知識庫、知識庫管理系統、推理機、綜合數據庫、自學習機制、解釋機制、人機介面等部分組成。其中最重要的是知識庫和推理機兩部分，這兩部分缺一不可。 -
While, some algorithms of machine learning are introduced to get the intelligence of the individual of hfutagent which makes individual skills in the robocup. finally, we realize the multi - agent cooperation mechanism using the knoledge of soccer experts. in our system, a typical cooperation method in robocup called sbsp is used, and we explains how to use reinforcement learning method to reach the goal of local cooperation, and the offense and defense strategy system is build by decision - theoretic
在本文中，首先介紹了典型的agent結構和mas模型和模擬機器人足球的一些主要模型：設計了一個分層的agent結構? hfutagent ，通過機器學習演算法實現了agent的個體智能；最後結合足球領域專家的知識實現了agent間的協作，其中使用了robocup中一個典型的協作方法- sbsp ，設計了一個通過強化學習的方法來達到agent之間的局部協作，把基於效用的對策論方法引入了hfutteam的進攻體系和防守體系中。 -
This article brings forward a new kind of machine - learning method ? extension machine method. in this method, according to the evaluation of the model in the system utilizing extension evaluation method, the model piles up experience in the continually us ing and obtains the exact knowledge about decision, corrects its parameter and ameliorate the arithmetic of itself. in this way, the model achieve the aim of perfecting its capability through self - learning
本文提出了一種新的機器學習方法? ?可拓機器方法，利用可拓評價方法對系統中的模型進行評估，根據評估結果，使模型在不斷使用過程中積累經驗，獲取與決策相關的正確知識，修正模型參數，改進模型演算法，從而使模型通過自我學習，達到逐步完善自身性能的目的。 -
Thirdly, by introducing fuzzy theory into system evaluation, evaluating student, teaching, course resource, and function of whole system. fourthly, making use of learning from examples based on information theory, machine learning algorithm is improved and machine learning decision tree is realized. finally, on reasoning mechanism, combining means of two classes reasoning is taken
第三，在系統評價中引入了模糊理論，對學生、教學、課程資源以及系統的整體功能進行了評價；第四，採用基於信息論的示例學習，改進了決策樹學習演算法，並建立了機器學習決策樹；第五，在推理機制上，採取兩級推理相結合的方法進行推理，即用基於語義網路的模糊推理確定教學序列，用基於產生式規則的推理確定教學方法，並給出了詳細的推理演算法。 -
The aims of this dissertation include : try to solve problems in rough set based knowledge discovery and machine learning ; build up knowledge model for complex industrial processes ; following the concepts and approaches of nonlinear system control, construct a control system framework based on rough state space ; apply rough set theory to fault detection and diagnosis ( fdd ). the main contributions of the dissertation are as follows : 1 reviewed the developments and research situation of rough set theory
本文的主要目的是試圖解決粗糙集在知識獲取、機器學習以及工業生產實際運用中所遇到一些主要問題，利用粗糙集在分析處理不完全、不精確和不一致數據中所具有的優勢，對復雜工業過程進行基於規則的非機理知識建模，在規則模型的基礎上，結合現代控制理論中的有關概念和方法，構造粗糙控制的初步框架，並將粗糙集方法運用於故障診斷。 -
The data mining techniques produce and develop quickly under the application environment. they can converse the sea data into the useful knowledge automatically and intelligently. the discovering methods synthesize the research achievements in the fields including expert system, machine learning, statistics, pattern recognition, database, etc. they can resolve the problems in the information and in favor of data ' s conversion
數據挖掘技術是一門交叉性學科，涉及到機器學習、模式識別、歸納推理、統計學、數據庫、數據可視化、高性能計算等多個領域，對解決在信息技術發展中存在的擁有大量數據但缺乏有用信息的問題，以及完成從業務數據到決策信息的轉換方面具有較強的功效。 -
Statistical learning theory ( slt ) is based on the structural risk minimization ( srm ) principle, and it is a new set of theory system, which specially aims at machine learning issues under the circumstances of small - sample. based on this slt, supporting vector machine ( svm ) method has been developed as a new machine learning algorithm and also practical applications of slt
統計學習理論建立在結構風險最小化原則基礎上，它是專門針對少樣本情況下機器學習問題而建立的一套新的理論體系，支持向量機就是在統計學習理論這一基礎上發展起來的一種新的機器學習演算法，它是統計學習理論的具體應用。 -
We attempt to exploit various machine - learning techniques to learn the heuristic knowledge from users " experiences, so that the image segmentation system can have some human ability in adaptively selecting optimal algorithm and corresponding parameters. learning based image segmentation system can be classified i
希望使用機器學習的技術，通過從用戶對訓練圖像集的分割和評價中學習相應的啟發式知識，以此使系統能夠根據圖像的特徵，為不同的圖像靈活的選擇參數或演算法，從而自動實現令人滿意的分割。 -
To realize the individuation service of web information, we need many domanial theoretics and techniques, for example, mostly, information searches, information filtration, computer network, distributed disposal, database manage system, data mining, numeric library, disposal ofnarural language, artificial intelligence, machine learning and so on. thus, to realize the individuation service of web information, we will be encountered great challenges and we have to do a compositive and hard task
要實現web的個性化服務，涉及到許多領域的理論和技術，主要有信息檢索、信息過濾、計算機網路、分散式處理、數據庫、數據挖掘、數字圖書館、自然語言處理、人工智慧和機器學習等，所以要實現web的個性化服務具有綜合性和挑戰性。 -
In the first part of this paper, knowledge search technology based on internet is introduced, web data mining and information search technology based on internet are discussed and machine learning based on internet is analyzed. in the second part, knowledge intelligent search system used in internet circumstance is designed and finally completed based on the work above, which includes modeling of intelligent search system and carrying out of respective function module
本文研究了基於網際網路的知識檢索技術，討論了基於internet的web數據挖掘和信息檢索技術，分析了基於internet的信息檢索的機器學習；在研究這些理論的基礎上對基於網際網路的知識智能檢索系統進行了設計和實現。 -
We explored the specific machine learning technique, i. e. bayesian technique in this paper, in the hope of automatically creating such kind of metadata from training data. we assigned wsdl documents to different categories using bayesian latent semantic model. with the frame of blsm, our system classified wsdl documents only by a few of latent class variables and no labeled data
本論文中基於貝葉斯技術的web服務分類演算法的主要思想是通過引入貝葉斯潛在語義模型，首先將含有潛在類別主題變量的wsdl文檔分配到相應的類主題中；接著利用樸素貝葉斯模型，結合前一階段的知識，完成對未含類主題變量的文檔作標注。 -
From the perspective of customers, this paper proposes web news hunter, the intelligent agent system, which uses the natural language processing, machine learning and web searching techniques to mine the news automatically according to the users " interests
本論文從用戶的角度出發，提出了webnewshunter智能系統，它集自然語言處理，機器學習和網路搜索技術於一身，根據用戶的喜好自動搜索新聞。 -
The problem of how to combine machine learning theories into automated negotiation system has got more attention recently
因此，將機器學習理論應用到自動談判系統中成為電子商務領域的最新研究課題。
分享友人