scholarly journals Collective orientation of an immobile fish school and effect on rheotaxis

2021 ◽  
Vol 103 (2) ◽  
Author(s):  
Renaud Larrieu ◽  
Catherine Quilliet ◽  
Aurélie Dupont ◽  
Philippe Peyla
Keyword(s):  
Fish School ◽  
Collective Orientation

Development of a German-Language Questionnaire to Measure Collective Orientation as an Individual Attitude

2017 ◽  
Vol 76 (3) ◽  
pp. 91-105 ◽  
Author(s):  
Vera Hagemann
Keyword(s):  
Team Performance ◽  
Reliability And Validity ◽  
Future Research ◽  
German Language ◽  
Team Members ◽  
Collective Orientation ◽  
Team Research ◽  
German Speaking ◽  
Individual Variables ◽  
The Individual

Abstract. The individual attitudes of every single team member are important for team performance. Studies show that each team member’s collective orientation – that is, propensity to work in a collective manner in team settings – enhances the team’s interdependent teamwork. In the German-speaking countries, there was previously no instrument to measure collective orientation. So, I developed and validated a German-language instrument to measure collective orientation. In three studies (N = 1028), I tested the validity of the instrument in terms of its internal structure and relationships with other variables. The results confirm the reliability and validity of the instrument. The instrument also predicts team performance in terms of interdependent teamwork. I discuss differences in established individual variables in team research and the role of collective orientation in teams. In future research, the instrument can be applied to diagnose teamwork deficiencies and evaluate interventions for developing team members’ collective orientation.

Improving the effectiveness of traditional education based on computer artificial intelligence and neural network system

2020 ◽  
pp. 1-11
Author(s):  
Wenjuan Ma ◽  
Xuesi Zhao ◽  
Yuxiu Guo
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Education Reform ◽  
Traditional Education ◽  
Machine Learning Algorithms ◽  
Local Optimum ◽  
Optimization Strategy ◽  
Fish School ◽  
Tlbo Algorithm ◽  
Neural Network System

The application of artificial intelligence and machine learning algorithms in education reform is an inevitable trend of teaching development. In order to improve the teaching intelligence, this paper builds an auxiliary teaching system based on computer artificial intelligence and neural network based on the traditional teaching model. Moreover, in this paper, the optimization strategy is adopted in the TLBO algorithm to reduce the running time of the algorithm, and the extracurricular learning mechanism is introduced to increase the adjustable parameters, which is conducive to the algorithm jumping out of the local optimum. In addition, in this paper, the crowding factor in the fish school algorithm is used to define the degree or restraint of teachers’ control over students. At the same time, students in the crowded range gather near the teacher, and some students who are difficult to restrain perform the following behavior to follow the top students. Finally, this study builds a model based on actual needs, and designs a control experiment to verify the system performance. The results show that the system constructed in this paper has good performance and can provide a theoretical reference for related research.

scholarly journals Common concern for the global ecological commons: solidarity with future generations?

2021 ◽  
pp. 004711782110362
Author(s):  
Marianne Takle
Keyword(s):  
Political Process ◽  
Future Generations ◽  
The Political ◽  
Four Dimensions ◽  
Political Processes ◽  
Agenda 2030 ◽  
Collective Orientation ◽  
Scholarly Contribution ◽  
Analytical Tools ◽  
Normative Content

This article elaborates on ideas concerning future generations and whether they are useful in understanding some aspects of the concern for the global ecological commons. The article’s main scholarly contribution is to develop analytical tools for examining what a concern for future generations would require of current generations. It combines the scholarly literature on future generations with that of solidarity. The ideas concerning future generations are interpreted in terms of an ideal typical concept of solidarity with future generations. This concept is divided into four dimensions: the foundation of solidarity, the objective of solidarity, the boundaries of solidarity and the collective orientation. By applying these four dimensions in the context of the political process leading to Agenda 2030, the potentials and limitations of the concept are evident. The article concludes that the absence of reciprocity between current and future generations and uncertainty about the future are both crucial issues, which cut across the four dimensions. We cannot expect anything from people who have not yet been born, and we do not know what preferences they will have. This shows the vulnerability of forward-looking appeals to solidarity with future generations. Nevertheless, such appeals to solidarity may give global political processes a normative content and direction and can thereby contribute to understanding common concerns for the global ecological commons.

Application of the Improved Grey Model in Power Load Forecasting

2014 ◽  
Vol 575 ◽  
pp. 658-661 ◽  
Author(s):  
Yun Liang Wang ◽  
Qiao Yu Li
Keyword(s):  
Load Forecasting ◽  
Grey Model ◽  
Background Sequence ◽  
Fish School ◽  
Power Load ◽  
Power Load Forecasting ◽  
Improved Model

This paper presents an improved grey model used in power load forecasting. In order to overcome the limitation of the traditional grey model GM(1,1), vector θ is introduced to modify the calculating formula for background sequence value in grey model and build a more adaptable model. Using artificial fish school algorithm can solve the value of vector θ . It reflects that the improved model has higher accuracy of load forecasting and has wider application by cases analysis.

scholarly journals Generation of Cooperation in Fish School.

2000 ◽  
Vol 40 (4) ◽  
pp. 234-238 ◽  
Author(s):  
Nobuo SANNOMIYA
Keyword(s):  
Fish School

scholarly journals Optimización de la Inyección de potencia desde micro generación distribuida en sistemas Eléctricos de distribución de baja tensión. Desarrollos teóricos de un modelo Hiperheurístico

Lámpsakos ◽  
2018 ◽  
pp. 55-67 ◽  
Author(s):  
Gustavo Alejandro Schweickardt
Keyword(s):  
Message Passing ◽  
Message Passing Interface ◽  
Fish School

Este artículo presenta los desarrollos teóricos de un Modelo HiperHeurístico para Optimizar la Inyección de Potencia proveniente de Micro-Generadores Distribuidos en Sistemas Eléctricos de Distribución de Energía (SEDE) en Baja Tensión (BT), focalizándose sobre los Paneles Solares Fotovoltaicos (MG FV). Implica una Optimización Combinatoria MultiObjetivo, en el que los Métodos Clásicos no producen buenas soluciones en el Dominio Determinístico, relativo a sus Variables de Control, y colapsan en el Dominio de Incertidumbres de Carácter no Estocástico asociadas a aquellas. Aquí, son descritos los conceptos generales de una estrategia bio-inspirada referida como HiperHeurística, con un Método de Aprendizaje Sustentado en Razonamiento, y cuyo dominio se compone de un Conjunto de MetaHeurísticas MultiObjetivo del tipo PSO incorporando una forma híbrida, AFS (Artificial Fish School) que exhibe características aptas para ser integrada, y permite resolver problemas de convergencia observados por el autor en trabajos previos. Adicionalmente, se introduce la paralelización del algoritmo, reemplazando su formulación primigeniamente secuencial, utilizando la plataforma conocida como MPI (Message Passing Interface).

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