Modern information technologies and the advent of machines powered by artificial intelligence (AI) have already strongly influenced the world of work in the 21st century. Computers, algorithms and software simplify everyday tasks, and it is impossible to imagine how most of our life could be managed without them. However, is it also impossible to imagine how most process steps could be managed without human force? The information economy characterised by exponential growth replaces the mass production industry based on economy of scales
標簽： AI-and-Robotics-IBA-GEI-April 2017
上傳時間： 2020-06-10
上傳用戶：shancjb
Forewords to books can play a variety of roles. One is to describe in more general terms what the book is about. That’s not really neces- sary, since Jim Sterne is a master at communicating complex topics in relatively simple terms.
標簽： Intelligence artificial Marketing for
上傳時間： 2020-06-10
上傳用戶：shancjb
n recent years, there have been many books published on power system optimization. Most of these books do not cover applications of artifi cial intelligence based methods. Moreover, with the recent increase of artifi cial intelligence applications in various fi elds, it is becoming a new trend in solving optimization problems in engineering in general due to its advantages of being simple and effi cient in tackling complex problems. For this reason, the application of artifi cial intelligence in power systems has attracted the interest of many researchers around the world during the last two decades. This book is a result of our effort to provide information on the latest applications of artifi cial intelligence to optimization problems in power systems before and after deregulation.
標簽： Intelligence artificial System Power in
上傳時間： 2020-06-10
上傳用戶：shancjb
Inventors have long dreamed of creating machines that think. This desire dates back to at least the time of ancient Greece. The mythical figures Pygmalion, Daedalus, and Hephaestus may all be interpreted as legendary inventors, and Galatea, Talos, and Pandora may all be regarded as artificial life ( , Ovid and Martin 2004 Sparkes 1996 Tandy 1997 ; , ; , ).
上傳時間： 2020-06-10
上傳用戶：shancjb
artificial Intelligence (AI) has undoubtedly been one of the most important buz- zwords over the past years. The goal in AI is to design algorithms that transform com- puters into “intelligent” agents. By intelligence here we do not necessarily mean an extraordinary level of smartness shown by superhuman; it rather often involves very basic problems that humans solve very frequently in their day-to-day life. This can be as simple as recognizing faces in an image, driving a car, playing a board game, or reading (and understanding) an article in a newspaper. The intelligent behaviour ex- hibited by humans when “reading” is one of the main goals for a subfield of AI called Natural Language Processing (NLP). Natural language 1 is one of the most complex tools used by humans for a wide range of reasons, for instance to communicate with others, to express thoughts, feelings and ideas, to ask questions, or to give instruc- tions. Therefore, it is crucial for computers to possess the ability to use the same tool in order to effectively interact with humans.
標簽： Embeddings Processing Language Natural in
上傳時間： 2020-06-10
上傳用戶：shancjb
artificial Intelligence (AI) is a big field, and this is a big book. We have tried to explore the full breadth of the field, which encompasses logic, probability, and continuous mathematics; perception, reasoning, learning, and action; and everything from microelectronic devices to robotic planetary explorers. The book is also big because we go into some depth. The subtitle of this book is “A Modern Approach.” The intended meaning of this rather empty phrase is that we have tried to synthesize what is now known into a common frame- work, rather than trying to explain each subfield of AI in its own historical context. We apologize to those whose subfields are, as a result, less recognizable.
標簽： A-Modern-Approach Intelligence
上傳時間： 2020-06-10
上傳用戶：shancjb
隨著人類社會的進步，科學技術(shù)的發(fā)展日新月異，模擬人腦神經(jīng)網(wǎng)絡的人工神經(jīng)網(wǎng)絡已取得了長足的發(fā)展。經(jīng)過半個多世紀的發(fā)展，人工神經(jīng)網(wǎng)絡在計算機科學，人工智能，智能控制等方面得到了廣泛的應用。當代社會是一個講究效率的社會，科技更新領(lǐng)域也是如此。在人工神經(jīng)網(wǎng)絡研究領(lǐng)域，算法的優(yōu)化顯得尤為重要，對提高網(wǎng)絡整體性能舉足輕重.BP神經(jīng)網(wǎng)絡模型是目前應用最為廣泛的一種神經(jīng)網(wǎng)絡模型，對于解決非線性復雜問題具有重要的意義。但是BP神經(jīng)網(wǎng)絡有其自身的一些不足（收斂速度慢和容易陷入局部極小值問題），在解決某些現(xiàn)實問題的時候顯得力不從心。針對這個問題，本文利用遺傳算法的并行全局搜索的優(yōu)勢，能夠彌補BP網(wǎng)絡的不足，為解決大規(guī)模復雜問題提供了廣闊的前景。本文將遺傳算法與BP網(wǎng)絡有機地結(jié)合起來，提出了一種新的網(wǎng)絡結(jié)構(gòu)，在穩(wěn)定性、學習性和效率方面都有了很大的提高。基于以上的研究目的，本文首先設計了BP神經(jīng)網(wǎng)絡結(jié)構(gòu)，在此基礎上，應用遺傳算法進行優(yōu)化，達到了加快收斂速度和全局尋優(yōu)的效果。本文借助MATLAB平臺，對算法的優(yōu)化內(nèi)容進行了仿真實驗，得出的效果也符合期望值，實現(xiàn)了對BP算法優(yōu)化的目的。關(guān)鍵詞：生物神經(jīng)網(wǎng)絡：人工神經(jīng)網(wǎng)絡；BP網(wǎng)絡；遺傳算法；仿真隨著電子計算機的問世及發(fā)展，人們試圖去了解人的大腦，進而構(gòu)造具有人類思維的智能計算機。在具有人腦邏輯推理延伸能力的計算機戰(zhàn)勝人類棋手的同時，引發(fā)了人們對模擬人腦信息處理的人工神經(jīng)網(wǎng)絡的研究。1.1研究背景人工神經(jīng)網(wǎng)絡（artificial Noural Networks，ANN）（注：簡稱為神經(jīng)網(wǎng)絡），是一種數(shù)學算法模型，能夠?qū)π畔⑦M行分布式處理，它模仿了動物的神經(jīng)網(wǎng)絡，是對動物神經(jīng)網(wǎng)絡的一種具體描述。這種網(wǎng)絡依賴系統(tǒng)的復雜程度，通過調(diào)節(jié)內(nèi)部大量節(jié)點之間的關(guān)系，最終實現(xiàn)信息處理的目的。人工神經(jīng)網(wǎng)絡可以通過對輸入輸出數(shù)據(jù)的分析學習，掌握輸入與輸出之間的潛在規(guī)則，能夠?qū)π聰?shù)據(jù)進行分析計算，推算出輸出結(jié)果，因為人工神經(jīng)網(wǎng)絡具有自適應和自學習的特性，這種學習適應的過程被稱為“訓練"。
標簽： 遺傳算法 bp神經(jīng)網(wǎng)絡 matlab
上傳時間： 2022-06-16
上傳用戶：jiabin
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