In the vision of smart cities, everything is highly connected with the aid of computational intelligence. Therefore, the cyber-physical society has been named a computational social system for a long time. Due to the high relation with vast populations’ national livelihood, agriculture will still serve as a core industry in the national economy. As a result, this study focused on an efficient forecasting method for the agriculture economy. In recent years, the conception of deep intelligence has received overall prevalence in academia because of its excellent performance in implementing intelligent information processing tasks. Hence, this paper utilized deep intelligence driven by neural networks and managed to investigate an efficient prediction method for the agriculture economy of computational social systems. To fit the time-series forecasting scene of the long-term development of the agriculture economy, the convolutional neural network model is slightly improved by revising its parallel structure into the recurrent format. Finally, simulations on realistic datasets are carried out to evaluate the proposed forecasting method.

Nowadays, frequent climate extremes exert a serious impact on agricultural production and social development, which is seldom studied in the previous literature. Production–Living–Ecological (PLE) is a useful analysis framework, and China is a suitable model for such study. This paper takes the Huai River Eco-Economic Belt (HREB), an important agricultural zone in China, to study the relationship among agricultural production (P), society (L), and climate change (E), which is referred to as APLE. This paper constructs a coupled coordination evaluation index system for the APLE system and uses coupling coordination degree models and geographic detector to study the spatial and temporal evolution of the coordinated development of 34 counties (cities) in the HREB from 2009 to 2018. The results show the following: (1) The development of the agricultural subsystem and the social subsystem formed a “scissors difference” from 2009 to 2014, and the three subsystems showed a slight upward trend during 2014–2018. (2) The coupling and coordinated development of the APLE system in the HREB was generally stable, and the coupling coordination degree was improved from low-grade and slightly uncoordinated to barely and primarily coordinated. Furthermore, the spatial differentiation of the coupling coordination degree shows a clear pattern of being high in the southeast and low in the northwest. (3) The main influencing factors are the drought and flood protection rate, the effective irrigation rate, the per capita electricity consumption in agriculture, the number of beds in healthcare facilities per 10,000 people, the per capita disposable income of urban residents, the annual average temperature, and the annual precipitation. (4) The spatial–temporal evolution of the coupling and coordinated development of the APLE system is the result of the comprehensive effect of internal driving forces such as food security, the consumption level of rural residents, and the development level of urbanization construction, and external driving forces such as government public welfare and natural conditions.

Background To vigorously promote the integrated development and mutual adaptation of agriculture and logistics is an important way to realize agricultural modernization and rural revitalization. Along with the policy support of agricultural industry chain and the steady rise of the demand for agricultural products market, the total amount of agricultural product logistics continues to increase, and the growth rate remains stable. With the booming development of "Internet + agriculture" and e-commerce platform, agricultural logistic market welcomes a new round of development opportunities, reaching several trillion yuan. Compared with the developed countries, our agricultural product logistics is still far behind. At present, only 15% of vegetables and fruits and 30% of fresh meat have professional logistic transportation, while most of the rest are still in the state of local and primitive. The gap of logistic environment construction and logistic elements determines the difference in final benefit of agricultural products. The purpose of this study is to find out the influence of logistic elements on regional agricultural economic growth, and whether the influence between neighboring regions presents "the same prosperity", "the same loss" or "sharing weal and woe". Methods Based on the panel data of the statistical yearbook of 31 provinces in China from 2005 to 2020, the spatial Durbin model was constructed under the spatial weight matrix of economic distance and economic geographical distance to conduct empirical analysis, and the internal factors of logistics industry, factor spillover effect and its impact on agricultural economic growth were studied. Results Results showed that: (1) considering economic distance factor, the spatial coefficient of the time-fixed effects model passed the significance test in eastern China. Considering economic geographic distance factors, the individual and double fixed effect models passed the significance test in central China, and all models passed the significance test in western China. (2) From the perspective of logistic infrastructure, AVLFA, HM, TN and RM had a positive effect on the growth of agricultural economy in eastern China, but LIAV is on the contrary. AVLFA had a positive effect on agricultural economic growth, but TN was on the contrary in central China. In western China, LIAV and TN promoted agricultural economy while HM and RM held back it. From the perspective of the volume of logistics activity, both eastern and central regions did not pass the significance test, but FA was tested by the double fixed effect model and showed negative in western China. From the perspective of control variables, FU, AO and PT all promoted agricultural economy in eastern China, and FU and AO did the same in central and western China. PT was invalid in central regions and hindered agricultural economy in western China, which was different. Conclusion From the perspective of spatial spillover effect decomposition, the eastern region presents "one prosperity and all prosperity, and sharing weal and woe", while the central and western regions present "one prosperity and all prosperity, and one lost and all lost". At last suggestions as formulating the overall plan for the development of regional logistics, paying attention to regional differences and promoting coordinated development of logistics and agriculture in light of local conditions, and paying attention to the spatial spillover effect of elements were put forward.