Estimation of fish school biomass in Northern Taean costal marine ranching area using acoustics

2021 ◽  
Vol 14 (1) ◽  
pp. 1-10
Author(s):  
Yeongjae LEE ◽  
Jungjae GUK ◽  
Tae-jong KANG ◽  
Eun-bi MIN ◽  
Doo-jin HWANG
Keyword(s):  
Fish School

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.

Statistical Characterization of Fish School Clutter

2007 ◽  
Author(s):  
Timothy K. Stanton ◽  
Dezhang Chu
Keyword(s):  
Statistical Characterization ◽  
Fish School

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).

scholarly journals REDUCTION OF ACTIVE POWER LOSS BY VOLITION PARTICLE SWARM OPTIMIZATION

2018 ◽  
Vol 6 (6) ◽  
pp. 346-356
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Reactive Power ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Test System ◽  
Swarm Optimization ◽  
Fish School ◽  
Exploration Exploitation ◽  
Power Problem

This paper projects Volition Particle Swarm Optimization (VP) algorithm for solving optimal reactive power problem. Particle Swarm Optimization algorithm (PSO) has been hybridized with the Fish School Search (FSS) algorithm to improve the capability of the algorithm. FSS presents an operator, called as collective volition operator, which is capable to auto-regulate the exploration-exploitation trade-off during the algorithm execution. Since the PSO algorithm converges faster than FSS but cannot auto-adapt the granularity of the search, we believe the FSS volition operator can be applied to the PSO in order to mitigate this PSO weakness and improve the performance of the PSO for dynamic optimization problems. In order to evaluate the efficiency of the proposed Volition Particle Swarm Optimization (VP) algorithm, it has been tested in standard IEEE 30 bus test system and compared to other reported standard algorithms.  Simulation results show that Volition Particle Swarm Optimization (VP) algorithm is more efficient then other algorithms in reducing the real power losses with control variables are within the limits.

scholarly journals PENGARUH INTENSITAS CAHAYA TERHADAP KETERTARIKAN GEROMBOLAN IKAN PELAGIS KECIL PADA MINI PURSE SEINE DI PERAIRAN PEMALANG JAWA TENGAH

2017 ◽  
Vol 13 (2) ◽  
pp. 125
Author(s):  
Erfind Nurdin ◽  
Mohammad Natsir ◽  
Hufiadi Hufiadi
Keyword(s):  
Light Intensity ◽  
Significant Influence ◽  
High Intensity ◽  
Purse Seine ◽  
North Coast ◽  
Fish School ◽  
The Third ◽  
Small Intensity ◽  
The Difference ◽  
Fishing Practices

Penggunaan intensitas cahaya pada unit penangkapan light fishing cenderung meningkat. Hal ini, didasari atas persepsi bahwa intensitas cahaya yang tinggi akan meningkatkan hasil tangkapan. Fenomena ini dijadikan suatu penelitian yang dilakukan selama 3 minggu pada bulan September 2004 di perairan Pemalang Jawa Tengah. Alat tangkap pukat cincin mini (mini purse seine) di pantai utara Jawa pada operasi penangkapan selain menggunakan rumpon juga mengggunakan cahaya sebagai alat bantu penangkapan. Pengukuran nilai intensitas lampu dilakukan dengan meggunakan LI COR 250 quantum meter (μmol sɹ mɲ) pada jumlah lampu yang berbeda, dan digunakan pula akustik EY 500 untuk memperoleh data sebaran dan gerombolan ikan yang berada dalam pengaruh cahaya lampu. Pada deteksi awal (A) ikan cenderung mengelompok pada lahan intensitas tinggi, deteksi ke 2 (B) pengelompokkan mulai terkonsentrasi dekat kapal, deteksi ke-3 (C) pengelompokkan ikan bertambah banyak, dan deteksi ke-4 (D) kelompok ikan berada pada lahan yang sangat memungkinkan untuk ditangkap. Dari hasil penelitian diperoleh laju tangkap (catch rate) 125,7 kg per tawur. Perbedaan jumlah lampu yang sedikit tidak menunjukkan pengaruh yang terlalu besar terhadap hasil tangkapan. The influence of light intensity to the light fishing practices commonly tends to increase. Fishermen believe that with the higher intensity of light the bigger catch they have. This phenomenon stimulated us to a research that during was done three weeks on September 2004 in Pemalang West Java. Mini purse seine is conduct at north coast of Java use payaos and light artificial for fish attractive. LI COR 250 quantum metre (μmol sɹ mɲ) was used for light intencity at different lamps amount and EY 500 acoustic to obtain the data of fish school in influence of lamp light. At the first detecting (A) fish school was concentrated in high intensity area, the second detecting (B) the concentration was closer to the ship, the third detecting (C) fish school increased, and the forth detecting (D) fish school was consentrated in catchable area. The results show that the cath rate was 125.7 kg per setting. The difference of lamps amount with a small intensity did not show significant influence to the catch haul.

Sign in / Sign up

Export Citation Format

Share Document