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Artificial neural ne的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列包括價格和評價等資訊懶人包
Artificial neural ne的問題，我們搜遍了碩博士論文和台灣出版的書籍，推薦寫的 Product Lifecycle Management. Green and Blue Technologies to Support Smart and Sustainable Organizations: 18th IFIP WG 5.1 Inter 和的 Computational Intelligence for Covid-19 and Future Pandemics: Emerging Applications and Strategies都 可以從中找到所需的評價。
這兩本書分別來自 和所出版 。
國立陽明交通大學 電子研究所 林詩淳所指導 何雅雯的 基於神經進化演算法之場效電晶體元件模型 （2021），提出Artificial neural ne關鍵因素是什麼，來自於場效電晶體、神經進化演算法、元件精簡模型、神經網絡。
而第二篇論文國立中央大學 水文與海洋科學研究所 劉說安、錢樺所指導 黎梅山的 遙測方法之土地熱通量研究 （2020），提出因為有 常態化差異潛熱指數、遙測、蒸發散的重點而找出了 Artificial neural ne的解答。
Product Lifecycle Management. Green and Blue Technologies to Support Smart and Sustainable Organizations: 18th IFIP WG 5.1 Inter
為了解決Artificial neural ne 的問題，作者 這樣論述：
Sustainability, Sustainable Development and Circular Economy.- Classification based on Machine learning to Support Decision Making in E-commerce for Reverse Logistics.- Impacts of the Sustainable Automotive Chain: Faced with the perspective of electromobility in consolidated markets in Germany, Unit
ed States and Japan.- A Comparative Study on Material Selection for Designing an Electric Last Mile Vehicle for Parcel Delivery.- Strategic Planning Model of the Integrated Development Process for Sustainable Products (PEPDIPS): qualitative and quantitative assessment.- The human-centered product-se
rvice development process allied to sustainability.- Disruptive innovation: digital transformation and sustainability approaches.- Biomimicry concepts used as an environmentally friendly solution for the selection of waste for health services.- Integrated product development process and green supply
chain management - Proposal for a preliminary model.- Sustainability and Information Technologies & Services.- Methodology for Commodity Cost Estimation Through Production Line Analysis and Simulation.- Conceptual design methodology for knitted fabrics.- Management of Laser‐Cut Sheet‐Metal Part Usi
ng Collaborative Robots.- Financial assistance in a capital-constrained cellphone supply chain.- Application of the AKO Agile Tool for Biomimetic Product Development: A Proposal to Improve Lids Fixation for Household Appliances.- Sustainable Software Engineering: an empirical study of the Brazilian
financial sector.- Analysis and modeling the intersection of Design for X techniques, Business strategies and Product Life-cycle Management.- Methodology to enhance the lifetime of mechanical system by utilizing parametric accelerated life testing.- An initial exploration of Lean and Sustainable Dev
elopment with a focus on Service.- Manufacturing Oriented Service Development Process Framework: Theoretical Construction. -Green and Blue Technologies.- Island Detection for Distributed Photovoltaic Systems: a Review of Methods and a Simulation Analysis.- Approach to the Green Multi-objective Vehic
le Routing Problem in Logistic Distribution.- Digital management of large building stocks: BIM and GIS integration-based systems.- Sustainable Product Development for discarded materials reuse: U-TURN approach.- Requirements and barriers in the process of food export from Brazil to Europe.- An Appro
ach for Extension of a Digital Business Ecosystem by Digital Twin.- Managing New Product Development in the Fashion Industry with PLM: a Market Server Based Classification.- The repurchase intention of organic food: comparison between a theoretical and a nested model.- The Sustainable Production Cha
in and the Practice of Corporate Social and Environmental Responsibility.- AI & Blockchain Integration with Enterprise Applications.- Barriers of blockchain technology adoption in viable digital supply chain.- Artificial Intelligence Framework for Electrode Wear Prediction in Resistance Spot Welding
.- Assessing the Predictions of Machine Learning Algorithms in an Industrial Application Through Counterfactual Generation.- Anomaly Detection in Blockchain-enabled Supply Chain: An Ontological Approach.- InnoCrowd, an AI based optimization of a crowdsourced product development.- Applied Artificial
Intelligence: Risk Mitigation Matters.- Smart Contracts Implementation based on Bidirectional Encoder Representations from Transformers.- Digital Twin Proposal to Support Remote Learning for Engineering.- Blockchain-based Manufacturing Supply Chain Management using HyperLedger Fabric.- Comparative e
valuation of product and service solutions in the context of Product-Service Systems and Technical Inheritance.- Proposal of a Fair Voting Classifier Using Multi-Objective Optimization.- Sequencing through a global decision instance based on a neural network.- Impact Assessment of Ensemble-Based Unb
alance Handling Techniques for Credit Scoring.- PLM Maturity, PLM
基於神經進化演算法之場效電晶體元件模型
為了解決Artificial neural ne 的問題，作者何雅雯 這樣論述：
人工神經網絡 (ANN)已被證實在建立元件精簡模型(Compact Model)方面是有效的。其對非線性數據擬合的優秀能力以及不需具備相關的物理知識就能有效模擬元件特性的優勢，使得人工神經網絡非常適合應用在新開發元件的元件精簡模型建構上。元件模型為了提高擬合精確度，往往會使用大型神經網絡，然而大量的模型參數也就是模型的權重和偏差也會增加大量的電路模擬時間。於是我們提出了一種神經進化演算法(Neuroevolution, NE)，其利用遺傳演算法(Genetic Algorithm, GA)來調整神經網絡結構，並使用ADAM，一種結合反向傳播算法及梯度下降法的權重優化演算法，來建立元件精簡模型
。我們提出的神經進化演算法所建構的場效電晶體模型會和廣泛應用在精簡模型的多層感知器 (MLP)模型進行比較。與具有相似參數數量的 MLP 模型相比，NE模型在大多數情況下具有較低的方均根誤差 (RMSE)。以次臨界轉換處理(Subthreshold-transformation)的數據為例，具有1595個參數的NE模型和1651個參數的MLP模型在測試集分別有9.24×10-7和1.94×10-5的誤差。因此，使用NE調整網絡結構於精簡模型的建立上具有其潛在應用價值。
Computational Intelligence for Covid-19 and Future Pandemics: Emerging Applications and Strategies
為了解決Artificial neural ne 的問題，作者 這樣論述：
Utku Kose is an Associate Professor at Suleyman Demirel University, Turkey. He received a B.S. degree in 2008 from the computer education of Gazi University, Turkey. He received an M.S. degree in 2010 from Afyon Kocatepe University, Turkey, and D.S./Ph. D. degree in 2017 from Selcuk University, Turk
ey. He has over 100 publications including journal articles, authored and edited books, proceedings, and reports. He is also one of the series editors of the Biomedical and Robotics Healthcare Series, CRC Press. His research interest areas are artificial intelligence, machine ethics, artificial inte
lligence safety, optimization, chaos theory, distance education, e-learning, computer education, and computer science. Junzo Watada received his B.Sc. and M.Sc. degrees in electrical engineering from Osaka City University, Japan, and his Ph.D. degree from Osaka Prefecture University, Japan. He is c
urrently a Professor at the Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, and Professor Emeritus at Waseda University. He received the Henri Coanda Medal Award from Inventico in Romania in 2002. He is a Life Fellow of the Japan Society for Fuzzy Theory and intellige
nt informatics (SOFT). Prof. Watada is an IEEE senior member, Executive Chair of ISME, WCICME, a vice-president and life member, Forum of Interdisciplinary Mathematics. He contributes to editing various international journals as an editorial board member of more than 30 journals. His professional in
terests include artificial neural networks, human-centric data mining, soft computing, tracking systems, knowledge engineering, financial engineering, and management engineering.Omer Deperlioglu received his B.Sc. in Electric and Electronic (1988) from Gazi University, M.Sc. in Computer Science (199
6) from Afyon Kocatepe University, Ph.D. in Computer Science (2001) from Gazi University. He is an Associate Professor of Computer Programming in the Department of Science, Vocational School of Afyon, Afyon Kocatepe University of Afyon, Turkey. His current research interests include different aspect
s of Artificial Intelligence applied in Power Electronics, Biomedical, and Signal Processing. He has edited a book and (co-) authored three books and over 50 papers.Jose Antonio Marmolejo is a Professor at Panamerican University, Mexico. He received his Doctorate in Operations Research (Hons) from t
he National Autonomous University of Mexico. At present, Prof. Marmolejo has the second-highest country-wide distinction granted by the Mexican National System of Research Scientists for scientific merit (SNI Fellow, Level 2). He is a member of the Network for Decision Support and Intelligent Optimi
zation of Complex and Large Scale Systems, Mexican Society for Operations Research, and System Dynamics Society. He has authored over thirty research articles in journals, books, and conference proceedings. His research areas are operations research, largescale optimization techniques, computational
techniques, analytical methods for planning, operations, and control of electric energy and logistic systems, sustainable supply chain design, and digital twins in supply chains.
遙測方法之土地熱通量研究
為了解決Artificial neural ne 的問題，作者黎梅山 這樣論述：
地表能量傳遞與轉換的過程在區域天氣、氣候和水循環中扮演著關鍵角色，而理解能量交換過程的特性對於提升許多應用的效率與效用相當重要，例如天氣預報系統、水文過程數值模擬、水資源管理、土地利用規劃、森林脆弱性評估等。長久以來，地面觀測一直被當作地表熱通量估算的逐點測量方法，但是其使用通常侷限於設定的地點，以及空間覆蓋範圍，從而導致難以在區域性的尺度操作。隨著以衛星為基礎的系統發展，空間科學和技術已成為全球觀測系統的關鍵要素，這為地-氣熱交換研究提供了高水準的時空效率、經濟效益之資料來源，根據來自遙測資料不同程度的輸入要求，已有許多不同的執行方法。以遙測資料為主要輸入，地表能量平衡模式中的物理過程方法
被廣泛用於估計陸-氣界面的能量交換。然而，這些方法涉及建立複雜的物理過程，並且仍然侷限於代表地面觀測系統的設定地點。多光譜遙測技術已被普遍用於收集影響陸-氣界面傳熱過程的地表特性，利用反射率的差異，可以藉由分析光譜反射率特性來了解地表特徵。在本研究中，提出了一種新的多光譜指數，即「常態化差異潛熱指數」（NDLI），用於從衛星影像中推估潛熱通量。它利用了綠色、紅色和短波紅外光三個波段的反射率觀測數值，而這三個波段通常用於衛星地球觀測任務。NDLI首先用於淬取台灣嘉義市東部子區域內陸-氣之間的熱傳遞訊號。與現有的其他遙測指標相比，NDLI與地表模型能量平衡式（SEBAL）計算出的潛熱通量具有最高的
相關性係數( r = 0.75)。 隨後，對NDLI進行檢驗並推估在越南太平省的地表蒸發散 (ET)。 結果表明，在98.1％的稻田中，NDLI推估的ET與SEBAL的推估結果相差不到10％。此外，NDLI推估的ET在逆境水稻區中呈現較低數值，顯示此方法之優越性。結論是，新開發的NDLI能夠量化地表的水可利用量，並且在需要陸-氣界面傳熱信息的各種實際應用中NDLI具有潛在的幫助作用。由於NDLI的方程式簡單易行，透過現有的大量衛星資料，可在其他感興趣的區域進行操作，並有助於多種實際應用