The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment ...The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment outcomes are highly complex phenomena that happen inside the human body.Decoding these states is significant for improving the quality of technology and providing an impetus to scientific research aimed at understanding the functioning of the human mind.One of the key advantages of quantum wave-functions over conventional classical models is the existence of configurable hidden variables,which provide more data density due to its exponential state-space growth.These hidden variables correspond to the amplitudes of each probable state of the system and allow for the modeling of various intricate aspects of measurable and observable physical quantities.This makes the quantum wave-functions powerful and felicitous to model cognitive states of the human mind,as it inherits the ability to efficiently couple the current context with past experiences temporally and spatially to approach an appropriate future cognitive state.This paper implements and compares some techniques like Variational Quantum Classifiers(VQC),quantum annealing classifiers,and hybrid quantum-classical neural networks,to harness the power of quantum computing for processing cognitive states of the mind by making use of EEG data.It also introduces a novel pipeline by logically combining some of the aforementioned techniques,to predict future cognitive responses.The preliminary results of these approaches are presented and are very encouraging with upto 61.53%validation accuracy.展开更多
Affected by the meteorological disasters and market fluctuations,the growing area,yield and quality of cotton in Shandong Province have been reduced to varying degrees in recent years.The majority of farmers are regar...Affected by the meteorological disasters and market fluctuations,the growing area,yield and quality of cotton in Shandong Province have been reduced to varying degrees in recent years.The majority of farmers are regarded as the main body of agricultural production,whose enthusiasm for growing cotton and confidence in the cotton market play a significant role in stabilizing the growing area and improving the quality of cotton.We randomly select the cotton farmers for in-depth interview,to understand the situation of cotton cultivation and their state of mind for growing,aimed at deriving the factors influencing farmers'willingness to grow cotton.In the future,it is necessary to make the best use of the advantages and bypass the disadvantages,and in a timely manner curb the decline of cotton cultivation in the process of guiding and encouraging the cotton cultivation,in order to solve the problems of low farmers'willingness to grow cotton and sluggish cotton industry from the root.展开更多
文摘The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment outcomes are highly complex phenomena that happen inside the human body.Decoding these states is significant for improving the quality of technology and providing an impetus to scientific research aimed at understanding the functioning of the human mind.One of the key advantages of quantum wave-functions over conventional classical models is the existence of configurable hidden variables,which provide more data density due to its exponential state-space growth.These hidden variables correspond to the amplitudes of each probable state of the system and allow for the modeling of various intricate aspects of measurable and observable physical quantities.This makes the quantum wave-functions powerful and felicitous to model cognitive states of the human mind,as it inherits the ability to efficiently couple the current context with past experiences temporally and spatially to approach an appropriate future cognitive state.This paper implements and compares some techniques like Variational Quantum Classifiers(VQC),quantum annealing classifiers,and hybrid quantum-classical neural networks,to harness the power of quantum computing for processing cognitive states of the mind by making use of EEG data.It also introduces a novel pipeline by logically combining some of the aforementioned techniques,to predict future cognitive responses.The preliminary results of these approaches are presented and are very encouraging with upto 61.53%validation accuracy.
基金Supported by Fund of Cotton Industrial Economic Experts of Modern Agricultural Technology System in Shandong Province[Shandong Agricultural Science and Technology(2012)No.26]Fund of Soft Science Research Base for Issues Concerning Agriculture and Countryside and Farmers in Shandong Province(2007RKA003)
文摘Affected by the meteorological disasters and market fluctuations,the growing area,yield and quality of cotton in Shandong Province have been reduced to varying degrees in recent years.The majority of farmers are regarded as the main body of agricultural production,whose enthusiasm for growing cotton and confidence in the cotton market play a significant role in stabilizing the growing area and improving the quality of cotton.We randomly select the cotton farmers for in-depth interview,to understand the situation of cotton cultivation and their state of mind for growing,aimed at deriving the factors influencing farmers'willingness to grow cotton.In the future,it is necessary to make the best use of the advantages and bypass the disadvantages,and in a timely manner curb the decline of cotton cultivation in the process of guiding and encouraging the cotton cultivation,in order to solve the problems of low farmers'willingness to grow cotton and sluggish cotton industry from the root.
