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The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to complete tasks through the cooperation of many agents. In this study, the evolution of crowd intelligence is studied through the clustering method and the particle swarm optimization (PSO) algorithm.

This study proposes a crowd evolution method based on intelligence level clustering. Based on clustering, this method uses the agents’ intelligence level as the metric to cluster agents. Then, the agents evolve within the cluster on the basis of the PSO algorithm.

Two main simulation experiments are designed for the proposed method. First, agents are classified based on their intelligence level. Then, when evolving the agents, two different evolution centers are set. Besides, this paper uses different numbers of clusters to conduct experiments.

The experimental results show that the proposed method can effectively improve the crowd intelligence level and the cooperation ability between agents.

This paper proposes a crowd evolution method based on intelligence level clustering, which is based on the clustering method and the PSO algorithm to analyze the evolution.

The purpose of this paper is to study the issue of contingency evolution of acquisition organization systems with the game group link method.

The concept and method of the game group link are used to analyze the evolution law of acquisition, to find a basis for the contingency evolution of acquisition organization system.

Studies prove that the contingency evolution of acquisition organization systems has the following basic laws: continuous evolution laws adapted to environmental requirements; laws of coordinated evolution as a whole, law of evolution from gradual change to sudden change; evolution path is determined by concrete situations; evolution pattern is determined by dynamic conditions; and law of evolution promoted by innovation.

Research results of this paper have significance in inspiration and theoretical instruction in respect of effectively increasing evolution profits of acquisition organization systems, promoting realization of purpose of acquisition organization systems, actively boosting evolution, and continuous development of acquisition organization systems.

It is shown that the acquisition process is the reasoning game process, development game process, and production game process conducted in turns by the main participating bodies of acquisition during the full life cycle of equipment. This process has clear features of “link,” and a correlated game link is formed among its different stages.

The paper proves that the acquisition process is a process of multi‐stage complex games and evolution game, with the full life cost control as the key issue in face of a fixed budget.

The purpose of this paper is to solve difficult estimation problem on aircraft sudden fault by proposing a new pre-estimating method according to the energy evolution degree of the sensitive parameters to estimate the sudden fault. The sudden fault affects seriously the flight safety of aircraft.

It is based on the dissipative structure theory, and the evolution process of energy parameters is utilized. First, the evolution key points of sudden fault are determined by the time-varying entropy of sensitive parameters and the frequency band energy distribution. Then, we can obtain the evolution degree of sample while the evolution key points import the logistic regression (LR) model, and one can establish the pre-estimation model by means of relevance vector machine (RVM). While the evolution feature vector imports the RVM pre-estimation model, one can pre-estimate the sudden fault of aircraft.

The simulation results showed that this method can not only track the evolution process of aircraft sudden fault but also estimate its evolution degree, and it has a higher pre-estimating accuracy.

It provides a new way to forecast the sudden fault and increase the security of aircraft.

This paper proposes a pre-estimating method on aircraft sudden fault. It is based on the dissipative structure theory and the energy-sensitive parameters of the sudden faults are used. This method can enhance the security of aircraft and increase the protective ability of sudden fault on aircraft.

Dyadic multi-dimensionality informs the variation that exists within and between network ties and suggests that ties are not all the same and not all equally strategic. This chapter presents a model of dyadic evolution grounded in dyadic multi-dimensionality and framed within actor-level, dyadic-level, endogenous, and exogenous contexts. These contexts generate both strategic catalysts that motivate network action and bounded agency that may constrain such network action. Assuming the need to navigate within bounded agency, the model highlights three strategic processes that demonstrate how dyadic multi-dimensionality underlies the evolution of strategic network ties.

Purpose – This chapter focuses on the role evolution has played in our development of politics and public policy and reviews the theoretical approaches and studies of the last decade that address biopolitics and evolution, such as the “gene-culture co-evolution theory.”

Design/methodology/approach – In this chapter some of these theoretical developments will be reviewed, including what has been called the “Synergism Hypothesis,” with particular emphasis on what is relevant for understanding the role of politics and public policy in the evolutionary process.

Findings – A new, multileveled paradigm has emerged in evolutionary biology during the past decade, one which emphasizes the role of cooperative phenomena in the evolution of complexity over time, including the evolution of socially organized species such as humankind. I refer to it as “Holistic Darwinism.”

Practical implications – This study develops an understanding of the complicated relationship between human biology and the role of evolution in shaping politics and public policy.

Originality/value – This study addresses several existing biopolitical concepts and presents new explanations and terminology for its understanding.

Under the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance.

Taking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized.

The research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down.

This research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development.

Research on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events.

This paper aims to propose a method for better discovering topic evolution path and semantic relationship from the perspective of patent entity extraction and semantic representation. On the one hand, this paper identifies entities that have the same semantics but different expressions for accurate topic evolution path discovery. On the other hand, this paper reveals semantic relationships of topic evolution for better understanding what leads to topic evolution.

Firstly, a Bi-LSTM-CRF (bidirectional long short-term memory with conditional random field) model is designed for patent entity extraction and a representation learning method is constructed for patent entity representation. Secondly, a method based on knowledge outflow and inflow is proposed for discovering topic evolution path, by identifying and computing semantic common entities among topics. Finally, multiple semantic relationships among patent entities are pre-designed according to a specific domain, and then the semantic relationship among topics is identified through the proportion of different types of semantic relationships belonging to each topic.

In the field of UAV (unmanned aerial vehicle), this method identifies semantic common entities which have the same semantics but different expressions. In addition, this method better discovers topic evolution paths by comparison with a traditional method. Finally, this method identifies different semantic relationships among topics, which gives a detailed description for understanding and interpretation of topic evolution. These results prove that the proposed method is effective and useful. Simultaneously, this method is a preliminary study and still needs to be further investigated on other datasets using multiple emerging deep learning methods.

This work provides a new perspective for topic evolution analysis by considering semantic representation of patent entities. The authors design a method for discovering topic evolution paths by considering knowledge flow computed by semantic common entities, which can be easily extended to other patent mining-related tasks. This work is the first attempt to reveal semantic relationships among topics for a precise and detailed description of topic evolution.

This paper extends the current literature on app engagement to identify dynamic factors that affect app engagement and the value-creation pathway that connect these factors with app engagement.

Survey data were collected from 299 app users to test the proposed research model.

The study found that the perceived effectiveness of evolution content and that of evolution speed impose both individual and joint positive effects on app identity, which serves as the mediation mechanism that connects these dynamic factors with app engagement.

This study takes the user perspective to explore how user perceptions of the effectiveness of app evolution content and speed, which represent unique user experiences in the app context, cultivate app engagement by enhancing app identity. Specifically, this study reveals the intertwined relationship among perceived effectiveness of app evolution, app identity, and app engagement.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.

The purpose of this paper is to examine how entrepreneurship culture affects start-up and venture capital co-evolution during the early evolution of an entrepreneurial ecosystem (EE) and its ability to foster the emergence of ambitious entrepreneurship as an outcome of its activity. Unlike studies that capture entrepreneurship culture at the national level, this study focusses specifically on the culture of venture capital-financed entrepreneurship and understanding its implications to the development of venture capital markets and successful firm-level outcomes within ecosystems.

Relying on EE and organisational imprinting theory, this study specifies characteristics of venture capital-financed entrepreneurship of Silicon Valley to illustrate the American way of building start-ups and examine whether they have as imprints affected to the entrepreneurship culture and start-up and venture capital co-evolution in Finland during the early evolution of its EE between 1980 and 1997.

The results illustrate venture capital-financed entrepreneurship culture as a specific example of entrepreneurship culture beneath the national level that can vary across geographies like the findings concerning Finland demonstrate. The findings show that this specific culture matters through having an impact on the structural evolution and performance of EEs and on the ways how they deliver or fail to deliver benefits to entrepreneurs.

The results show that venture capital-financed entrepreneurship and the emergence of success stories as outcomes of start-up and venture capital co-evolution within an EE are connected to a specific type of entrepreneurship culture. This paper also contributes to the literature by connecting the fundamentals of organisational imprinting to EE research.