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    Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives

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    [EN] Digital transformation provide supply chains (SCs) with extensive accurate data that should be combined with analytical techniques to improve their management. Among these techniques Artificial Intelligence (AI) has proved their suitability, memory and ability to manage uncertain and constantly changing information. Despite the fact that a number of AI literature reviews exist, no comprehensive review of reviews for the SC operations planning has yet been conducted. This paper aims to provide a comprehensive review of AI literature reviews in a structured manner to gain insights into their evolution in incorporating new ICTs and collaboration. Results show that hybrization man-machine and collaboration and ethical aspects are understudied.This research has been funded by the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE). 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    Taguchi Method and Artificial Neuro-Fuzzy Inference System (ANFIS) based Validation of Enzyme Production: A review

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    Numbers of reports on enzyme production enhancements (from bacteria and fungi) are present in the literature by using One Variable at Time (OVAT) based optimization of medium components. OVAT strategy is not suitable for the cost-effective production of enzymes in lieu of modern statistical and artificially intelligent techniques like Response Surface Methodology (RSM), Taguchi Method and Artificial Neural Network (ANN) and Artificial Neuro-Fuzzy Inference System (ANFIS) etc. The Taguchi Method and ANFIS enzyme yield prediction results are in consonance with those produced by the RSM system and in fact are more closer to the actual enzyme yield. This shows the application of the proposed system in enzyme yield prediction given a set of parameter values

    Managing smart cities with deepint.net

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    In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems. It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities
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