通智测试——基于动态具身物理社会交互环境的通用人工智能测试

The release of the generative pre-trained transformer(GPT)series has brought artificial general intelligence(AGI)to the forefront of the artificial intelligence(AI)field once again.However,the questions of how to define and evaluate AGI remain unclear.This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions(DEPSI).More specifically,we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system.The Tong test describes a value-and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI,allowing for infinite task generation.We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized,quantitative,and objective benchmarks and evaluation of AGI.

Research on the Application of Intelligent Evaluation and Teacher-student Cooperation Assessment System in Teaching English Writing

Low efficiency in teaching and time-consuming in writing evaluation are two big problems for college English teachers.Therefore,it is necessary to create a new teaching model to solve these problems existing in traditional classroom-based teaching.This research adopts the research methods of test comparison before and after the students’composition experiment,questionnaire and semi-open interviews.Empirical research on a new teaching model that integrates the intelligent composition review and reform system represented by Piangai.com and the collaborative evaluation of teachers and students is conducted.The research results show that the new writing teaching model improves the quality of students’writing,promotes students’learning initiative,and enhances students’writing self-efficacy.This writing teaching model provides ideas for solving the problem of time-consuming and inefficient English writing teaching in large classes.

Effect Evaluation and Intelligent Prediction of Power Substation Project Considering New Energy

The evaluation of the implementation effect of the power substation project can find out the problems of the project more comprehensively,which has important practical significance for the further development of the power substation project.To ensure accuracy and real-time evaluation,this paper proposes a novel hybrid intelligent evaluation and prediction model based on improved TOPSIS and Long Short-Term Memory(LSTM)optimized by a Sperm Whale Algorithm(SWA).Firstly,under the background of considering the development of new energy,the influencing factors of power substation project implementation effect are analyzed from three aspects of technology,economy and society.Moreover,an evaluation model based on improved TOPSIS is constructed.Then,an intelligent prediction model based on SWA optimized LSTM is designed.Finally,the scientificity and accuracy of the proposed model are verified by empirical analysis,and the important factors affecting the implementation effect of power substation projects are pointed out.

Sustainability Intelligent Evaluation of Regional Microgrid Interconnection System Based on Combination Entropy Weight Rank Order-TOPSIS and NILA-KELM

Sustainability evaluation of regional microgrid interconnection system is conducive to a profound and comprehensive understanding of the impact of interconnection system projects.In order to realize the comprehensive and scientific intelligent evaluation of the system,this paper proposes an evaluation model based on combination entropy weight rank order-technique for order preference by similarity to an ideal solution(TOPSIS)and Niche Immune Lion Algorithm-Extreme Learning Machine with Kernel(NILAKELM).Firstly,the sustainability evaluation indicator system of the regional microgrid interconnection system is constructed fromfour aspects of economic,environmental,social,and technical characteristics,and the evaluation indicators are explained.Then,the classical evaluationmodel based on TOPSIS is constructed,and the entropy weight method and rank order method(RO)are coupled to obtain the indicator weight.The niche immune algorithm is used to improve the lion algorithm,and the improved lion algorithm is used to optimize the parameters of KELM,and the intelligent evaluation model based on NILA-KELM is obtained to realize fast real-time calculation.Finally,the scientificity and accuracy of themodel proposed in this paper are verified.The model proposed in this paper has the lowest RMSE,MAE and RE values,indicating that its intelligent evaluation results are the most accurate.This study is conducive to the horizontal comparison of the overall performance of regional microgrid interconnection system projects,helps investors to choose the most promising project scheme,and helps the government to find feasible project.

Rapid intelligent evaluation method and technology for determining engineering rock mass quality

The evaluation of engineering rock mass quality is fundamental work for the engineering activities of rock mass.The increasing scale of rock mass engineering necessitates higher intelligence,timeliness,and accuracy in engineering rock mass quality evaluation.As the core aspects of engineering rock mass quality evaluation,the structural characteristics,mechanical characteristics,and quality classification of rock mass have been innovated in recent years.The non-contact measurement technology for rock mass structure and rapid interpretation of rock mass structure information enables the intelligent extraction and analysis of rock mass structure parameters.The modular backpack laboratory system of rock mechanics provides an effective means to acquire rock mechanical parameters on-site conveniently.The theory of statistical mechanics of rock mass(SMRM)integrates various factors such as the rock mass properties,geological environment,and engineering disturbance,providing a theoretical basis for accurately evaluating the weakening and anisotropy of rock mass.The cloud computing platform established based on SMRM can provide technical support for the rapid calculation of rock mass parameters and instant evaluation of the rock mass quality.The development of intelligent evaluation method and technology is altering the conventional technical state of qualitative and semi-quantitative evaluation of engineering rock mass quality,supporting the realization of rock mass engineering construction with intellectualization and informatization.

Mechanism and application of an online intelligent evaluation model for energy consumption of a reheating furnace

An online model was proposed to identify the reasons behind changes in the energy consumption of the reheating furnace of a steel processing plant.The heat conversion of the furnace was analyzed and integrated with the fuel consumption of the furnace to obtain a model of the energy consumption.Combined with the mechanism analysis,the basic parameters affecting energy consumption were determined,and four key influencing factors were obtained:furnace output,furnace charging temperature,furnace tapping temperature,and steel type.The specific calculation method of the contribution of each influencing factor was derived to define the conditions of the baseline energy consumption,while the online data were used to calculate the energy value and the actual performance value of the baseline energy consumption.The contribution of each influencing factor was determined through normalization.The cloud platform was used for database reconstruction and programming to realize the online intelligent evaluation of the energy consumption of the reheating furnace.Finally,a case study of the evaluation of the practical energy consumption of a steel rolling furnace in a steel plant was presented.The intelligent evaluation results were quantified and displayed online,and the performance of the system in reducing production line energy consumption was demonstrated.