this paper proposes a novel control approach based on gradient descent methods to solve the problem of cooperative adaptive optimal output regulation of continuous-time linear multi-agent systems. this proposed approa...
详细信息
ISBN:
(纸本)9798350363029;9798350363012
this paper proposes a novel control approach based on gradient descent methods to solve the problem of cooperative adaptive optimal output regulation of continuous-time linear multi-agent systems. this proposed approach calculates gradients through online data rather than model information, such that a data-driven distributed adaptive controller is developed by adaptive dynamic programming, which ensures that each follower can achieve asymptotic tracking and disturbance rejection. Finally, the effectiveness of the proposed control algorithm is verified by simulation of connected and autonomous vehicles.
In thailand, demand for organic pork has emerged in recent years because of consumer concerns for health and the environment. Consequently, this creates a demand for organic feed for swine. this paper provides a linea...
详细信息
ISBN:
(纸本)9781728167855
In thailand, demand for organic pork has emerged in recent years because of consumer concerns for health and the environment. Consequently, this creates a demand for organic feed for swine. this paper provides a linear programming model for an organic feed mix problem. the model considers a set of non-organic and organic raw materials (RMs) withtheir supply availabilities and organic RMs percentage in dry weight. An optimal feed formulation is determined to satisfy nutrient requirements and organic proportion of the feed, as well as to minimize their total RMs purchase and pre-processing costs. A numerical example is given to demonstrate the model use.
We present an evolutionary algorithm for the induction of context-free grammars from positive and negative examples. the algorithm is based on genetic programming and uses a local optimization operator that is capable...
详细信息
ISBN:
(纸本)9780769529769
We present an evolutionary algorithm for the induction of context-free grammars from positive and negative examples. the algorithm is based on genetic programming and uses a local optimization operator that is capable of improving the learning task. Ordinary genetic operators were modified so as to bias the search and a new operator was proposed the system was evaluated using benchmark problems and results were compared with another recent approach. Results show that the proposed approach is very promising.
We present a technique for partitioning an audio file into maximally-sized segments having nearly uniform spectral content, ideally corresponding to notes or chords. Our method uses dynamic programming to globally opt...
详细信息
A bi-level programming model is constructed for the oilfield development in this paper withthe objective to maximize the total benefit. the management level of the oil company is regarded as the leader in this model,...
详细信息
A bi-level programming model is constructed for the oilfield development in this paper withthe objective to maximize the total benefit. the management level of the oil company is regarded as the leader in this model, which makes the global programming and assigns the allocated investments to four oilfield development modes (the follower). the lower levels work out their own optimized plans according to the tasks and the investment constraints, and then feed back to the upper level. To solve this mixed integer nonlinear programming problem, the Interactive Intuitionistic Fuzzy methods are employed to obtain the solution by combining withthe intuitionistic fuzzy sets and establishing a scoring function. A practical example from some Oilfield in China is used to illustrate the application of the method for the "14th Five-year Plan". (C) 2020 the Authors. Published by Elsevier B.V. this is an open access article under the CC BY-NC-ND license (http://***/licenses/by-ne-nd/4.0/) Peer-review under responsibility of the scientific committee of the 7thinternationalconference on Information Technology and Quantitative Management (ITQM 2019)
the problem of representing and learning complex visual stimuli in the context of modeling the process of conditional reflex formation is considered. the generative probabilistic framework is chosen which has been rec...
详细信息
the problem of representing and learning complex visual stimuli in the context of modeling the process of conditional reflex formation is considered. the generative probabilistic framework is chosen which has been recently successfully applied to cognitive modeling. A model capable of learning different visual stimuli is developed in the form of a program in Church (probabilistic programming language). NAO robot is programmed to detect visual stimuli, to point at selected stimuli in a sequence of trials, and to receive reinforcement signals for correct choices. Conducted experiments showed that the robot can learn stimuli of different types showing different decision-making behavior in a series of trial that could help arranging psychophysiological experiments.
the stock market is one of the best channels for financial development that requires a high accuracy prediction of the trades. this subject needs some technical skills and experience to achieve the best result. this p...
详细信息
ISBN:
(纸本)9781665403504
the stock market is one of the best channels for financial development that requires a high accuracy prediction of the trades. this subject needs some technical skills and experience to achieve the best result. this paper represents a tuned Python console program based on the Neural Network (NN), and the Artificial Intelligence (AI) to predict future price in a qualified and quantized way with high accuracy and close to real. New ideas implemented in this paper are combining AI and NN model in the Python console system with a security shell that works with voice and PIN to authenticate the user. It has Cross-Platform capability and supports cryptocurrencies price and their predictions. this program enables the user to have a duplication of the final data in his/her given email. the proposed approach presents the influence of AI and Machine learning in nearly future predictions. this system can be used in the all kinds of subjects that include past time databases.
Instruction scheduling is an important issue in the compiler optimization for embedded systems. the instruction scheduling problem is mainly solved heuristically since finding an optimal solution requires significant ...
详细信息
ISBN:
(纸本)9781424425389
Instruction scheduling is an important issue in the compiler optimization for embedded systems. the instruction scheduling problem is mainly solved heuristically since finding an optimal solution requires significant computational resources and, in general, the problem of optimally scheduling instructions is known to be NP-Complete. the development of processors with pipelines and multiple functional units has increased the demands on compiler writers to write complex instruction scheduling algorithms. these algorithms are required to ensure that the most efficient use of resources, i.e. the functional units and pipelines of the processor, is made due to the increased complexity of processor architectures. In this paper, the specific problem of automatically creating instruction scheduling heuristics is addressed.
Pattern classification is one of the most researched problems in Artificial Intelligence. Genetic programming (GP) has been used to construct classifiers by many researchers. Function Sequence Genetic programming (FSG...
详细信息
暂无评论