target="_blank" rel="nofollow" href="#note268" type="note">268.
Computer-automated design (CAutoD) – design automation usually refers to electronic design automation, or Design Automation which is a Product Configurator. Extending Computer-Aided Design (CAD), automated design and computer-automated designare concerned with a broader range of applications, such as automotive engineering, civil engineering, composite material design, control engineering, dynamic system identification and optimization, financial systems, industrial equipment, mechatronic systems, steel construction, structural optimisation, and the invention of novel systems. More recently, traditional CAD simulation is seen to be transformed to CAutoD by biologically inspired machine learning, including heuristic search techniques such as evolutionary computation, and swarm intelligence algorithms269.
Computing modules are plug-in specialized computers designed to solve narrowly focused tasks, such as accelerating the work of artificial neural networks algorithms, computer vision, voice recognition, machine learning and other artificial intelligence methods, built on the basis of a neural processor – a specialized class of microprocessors and coprocessors (processor, memory, data transfer).
Computing system is a software and hardware complex intended for solving problems and processing data (including calculations) or several interconnected complexes that form a single infrastructure270.
Computing units are blocks that work like a filter that transforms packets according to certain rules. The instruction set of the calculator can be limited, which guarantees a simple internal structure and a sufficiently high speed of operation271.
Сoncept drift in predictive analytics and machine learning, the concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions become less accurate as time passes272.
Сonnectionism is an approach in the fields of cognitive science, that hopes to explain mental phenomena using artificial neural networks273,274.
Сonsistent heuristic in the study of path-finding problems in artificial intelligence, a heuristic function is said to be consistent, or monotone, if its estimate is always less than or equal to the estimated distance from any neighboring vertex to the goal, plus the cost of reaching that neighbor275.
Сonstrained conditional model (CCM) is a machine learning and inference framework that augments the learning of conditional (probabilistic or discriminative) models with declarative сonstraints276.
Constraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses277.
Constraint programming is a programming paradigm wherein relations between variables are stated in the form of constraints. Constraints differ from the common primitives of imperative programming languages in that they do not specify a step or sequence of steps to execute, but rather the properties of a solution to be found278.
Constructed language (also conlang) is a language whose phonology, grammar, and vocabulary are consciously devised, instead of having developed naturally. Constructed languages may also be referred to as artificial, planned, or invented languages279.
Control theory in control systems engineering, is a subfield of mathematics that deals with the control of continuously operating dynamical systems in engineered processes and machines. The objective is to develop a control model for controlling such systems using a control action in an optimum manner without delay or overshoot and ensuring control stability280.
Convolutional neural network (CNN, or ConvNet) in deep learning, is a class of deep neural networks, most commonly applied to analyzing visual imagery. CNNs use a variation of multilayer perceptrons designed to require minimal preprocessing. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics. Сonvolutional neural network is a class of artificial neural network most commonly used to analyze visual images. They are also known as Invariant or Spatial Invariant Artificial Neural Networks (SIANN) based on an architecture with a common weight of convolution kernels or filters that slide over input features and provide equivalent translation responses known as feature maps281.
Confidentiality of information is a mandatory requirement for a person who has access to certain information not to transfer such information to third parties without the consent of its owner282.
Confirmation Bias – the tendency to search for, interpret, favor, and recall information in a way that confirms one’s own beliefs or hypotheses while giving disproportionately less attention to information that contradicts it283.
Confusion matrix is a situational analysis table that summarizes the prediction results of a classification model in machine learning. The records in the dataset are summarized in a matrix according to the real category and the classification score made by the classification model284,285.
Consumer artificial intelligence is specialized artificial intelligence programs embedded in consumer devices and processes286.
Continuous feature is a floating-point feature with an infinite range of possible values. Contrast with discrete feature287,288.
Contributor is a human worker providing annotations on the Appen data annotation platform289.
Convenience sampling – using a dataset not gathered scientifically in order to run quick experiments. Later on, it’s essential to switch to a scientifically gathered dataset290.
Convergence – informally, often refers to a state reached during training in which training loss and validation loss change very little or not at all with each iteration after a certain number of iterations. In other words, a model reaches convergence when
Computer-automated design [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Computer-automated_design (дата обращения: 04.05.2023)
Вычислительная система [Электронный ресурс] https://ru.wikipedia.org URL: https://cdto.wiki/Вычислительная_система (дата обращения: 28.03.2023)
Вычислительные блоки [Электронный ресурс] https://www.osp.ru URL: https://www.osp.ru/os/1997/06/179341 (дата обращения: 28.03.2023)
Сoncept drift [Электронный ресурс] https://deepchecks.com URL: https://deepchecks.com/how-to-detect-concept-drift-with-machine-learning-monitoring/ (дата обращения 12.03.2022)
Сonnectionism [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Connectionism (дата обращения: 04.05.2023)
Коннекционизм [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Коннекционизм (дата обращения: 04.05.2023)
Сonsistent heuristic [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Consistent_heuristic (дата обращения: 26.06.2023)
Constrained conditional model [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Constrained_conditional_model (дата обращения: 07.07.2022)
Сonstraint logic programming [Электронный ресурс] www.definitions.net URL: https://www.definitions.net/definition/Constraint (дата обращения 28.02.2022)
Сonstraint programming [Электронный ресурс] www.definitions.net URL: https://www.definitions.net/definition/Constraint (дата обращения 28.02.2022)
Искусственные языки [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Портал:Искусственные_языки (дата обращения: 02.05.2023)
Сontrol theory [Электронный ресурс] www.semanticscholar.org URL: https://www.semanticscholar.org/paper/Modern-control-systems-theory-Leondes-青木/c0fb8d86dec3dc0d09c207fa9888369328b766a9 (дата обращения 06.04.2022)
Сonvolutional neural network (CNN, or ConvNet) [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Convolutional_neural_network (дата обращения: 30.06.2023)
Конфиденциальность информации [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Конфиденциальность (дата обращения: 04.05.2023)
Предвзятость подтверждения [Электронный ресурс] https://te-st.ru URL: https://te-st.ru/2019/11/29/why-is-artificial-intelligence-biased/ (дата обращения: 04.02.2022)
Confusion matrix [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Confusion_matrix (дата обращения: 10.05.2023)
Confusion matrix [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#confusion-matrix (дата обращения: 10.05.2023)
Бытовой искусственный интеллект [Электронный ресурс] https://apr.moscow URL: https://apr.moscow/content/data/6/11 Технологии искусственного интеллекта. pdf (дата обращения: 28.03.2023)
Continuous feature [Электронный ресурс] https://www.primeclasses.in URL: https://www.primeclasses.in/glossary/data-science-course/machine-learning/continuous-feature (дата обращения: 11.05.2023)
Непрерывная функция [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Непрерывная_функция (дата обращения: 11.05.2023)
Contributor [Электронный ресурс] https://bigdataanalyticsnews.com URL: https://bigdataanalyticsnews.com/artificial-intelligence-glossary/ (дата обращения: 02.07.2023)
Convenience sampling [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#convenience-sampling (дата обращения 04.07.2023)
