scholarly journals Bringing a Time–Depth Perspective to Collective Animal Behaviour

2016 ◽  
Vol 31 (7) ◽  
pp. 550-562 ◽  
Author(s):  
Dora Biro ◽  
Takao Sasaki ◽  
Steven J. Portugal
Keyword(s):  
Animal Behaviour ◽  
Collective Animal Behaviour

scholarly journals Red deer synchronise their activity with close neighbours

2013 ◽  
Author(s):  
Sean A Rands ◽  
Naomi Terry ◽  
Hayley Muir
Keyword(s):  
Social Relationships ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Animal Behaviour ◽  
The Third ◽  
Collective Animal Behaviour ◽  
Made In

Models of collective animal behaviour frequently make assumptions about the effects of neighbours on the behaviour of focal individuals, but these assumptions are rarely tested. One such set of assumptions is that the switch between active and inactive behaviour seen in herding animals is influenced by the activity of close neighbours, where neighbouring animals show a higher degree of behavioural synchrony than would be expected by chance. We tested this assumption by observing the simultaneous behaviour of paired individuals within a herd of red deer Cervus elaphus. Focal individuals were more synchronised with their two closest neighbours than with the third closest or randomly selected individuals from the herd. Our results suggest that the behaviour of individual deer is influenced by immediate neighbours. Even if we assume that there are no social relationships between individuals, this suggests that the assumptions made in models about the influence of neighbours may be appropriate.

The STARFLAG handbook on collective animal behaviour: 2. Three-dimensional analysis

2008 ◽  
Vol 76 (1) ◽  
pp. 237-248 ◽  
Author(s):  
Andrea Cavagna ◽  
Irene Giardina ◽  
Alberto Orlandi ◽  
Giorgio Parisi ◽  
Andrea Procaccini
Keyword(s):  
Dimensional Analysis ◽  
Three Dimensional ◽  
Animal Behaviour ◽  
Collective Animal Behaviour

scholarly journals Optimized Hyper Beamforming of Linear Antenna Arrays Using Collective Animal Behaviour

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Gopi Ram ◽  
Durbadal Mandal ◽  
Rajib Kar ◽  
Sakti Prasad Ghoshal
Keyword(s):  
Antenna Arrays ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Beam Width ◽  
Animal Behaviour ◽  
Linear Antenna ◽  
Sidelobe Level ◽  
Real Coded Genetic Algorithm ◽  
Linear Antenna Arrays ◽  
Collective Animal Behaviour

A novel optimization technique which is developed on mimicking the collective animal behaviour (CAB) is applied for the optimal design of hyper beamforming of linear antenna arrays. Hyper beamforming is based on sum and difference beam patterns of the array, each raised to the power of a hyperbeam exponent parameter. The optimized hyperbeam is achieved by optimization of current excitation weights and uniform interelement spacing. As compared to conventional hyper beamforming of linear antenna array, real coded genetic algorithm (RGA), particle swarm optimization (PSO), and differential evolution (DE) applied to the hyper beam of the same array can achieve reduction in sidelobe level (SLL) and same or less first null beam width (FNBW), keeping the same value of hyperbeam exponent. Again, further reductions of sidelobe level (SLL) and first null beam width (FNBW) have been achieved by the proposed collective animal behaviour (CAB) algorithm. CAB finds near global optimal solution unlike RGA, PSO, and DE in the present problem. The above comparative optimization is illustrated through 10-, 14-, and 20-element linear antenna arrays to establish the optimization efficacy of CAB.

Collective Animal Behaviour Based Optimization Algorithm for IIR System Identification Problem

2014 ◽  
Vol 5 (1) ◽  
pp. 1-35
Author(s):  
P. Upadhyay ◽  
R. Kar ◽  
D. Mandal ◽  
S. P. Ghoshal
Keyword(s):  
System Identification ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Identification Problem ◽  
Animal Behaviour ◽  
Infinite Impulse Response ◽  
Present System ◽  
Real Coded Genetic Algorithm ◽  
Identification Approach ◽  
Collective Animal Behaviour

In this paper a novel optimization technique which is developed on mimicking the collective animal behaviour (CAB) is applied to the infinite impulse response (IIR) system identification problem. Functionality of CAB is governed by occupying the best position of an animal according to its dominance in the group. Enrichment of CAB with the features of randomness, stochastic and heuristic search nature has made the algorithm a suitable tool for finding the global optimal solution. The proposed CAB has alleviated from the defects of premature convergence and stagnation, shown by real coded genetic algorithm (RGA), particle swarm optimization (PSO) and differential evolution (DE) in the present system identification problem. The simulation results obtained for some well known benchmark examples justify the efficacy of the proposed system identification approach using CAB over RGA, PSO and DE in terms of convergence speed, unknown plant coefficients and mean square error (MSE) values produced for IIR system models of both the same order and reduced order.

The STARFLAG handbook on collective animal behaviour: 1. Empirical methods

2008 ◽  
Vol 76 (1) ◽  
pp. 217-236 ◽  
Author(s):  
Andrea Cavagna ◽  
Irene Giardina ◽  
Alberto Orlandi ◽  
Giorgio Parisi ◽  
Andrea Procaccini ◽  
...  
Keyword(s):  
Animal Behaviour ◽  
Empirical Methods ◽  
Collective Animal Behaviour

scholarly journals Red deer synchronise their activity with close neighbours

2013 ◽  
Author(s):  
Sean A Rands ◽  
Naomi Terry ◽  
Hayley Muir
Keyword(s):  
Social Relationships ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Animal Behaviour ◽  
The Third ◽  
Collective Animal Behaviour ◽  
Made In

Models of collective animal behaviour frequently make assumptions about the effects of neighbours on the behaviour of focal individuals, but these assumptions are rarely tested. One such set of assumptions is that the switch between active and inactive behaviour seen in herding animals is influenced by the activity of close neighbours, where neighbouring animals show a higher degree of behavioural synchrony than would be expected by chance. We tested this assumption by observing the simultaneous behaviour of paired individuals within a herd of red deer Cervus elaphus. Focal individuals were more synchronised with their two closest neighbours than with the third closest or randomly selected individuals from the herd. Our results suggest that the behaviour of individual deer is influenced by immediate neighbours. Even if we assume that there are no social relationships between individuals, this suggests that the assumptions made in models about the influence of neighbours may be appropriate.

scholarly journals The Role of Individual Heterogeneity in Collective Animal Behaviour

2020 ◽  
Vol 35 (3) ◽  
pp. 278-291 ◽  
Author(s):  
Jolle W. Jolles ◽  
Andrew J. King ◽  
Shaun S. Killen
Keyword(s):  
Animal Behaviour ◽  
Individual Heterogeneity ◽  
Collective Animal Behaviour

Collective-Animal-Behaviour-Based Optimized Null Placement in Time-Modulated Linear Antenna Arrays

2017 ◽  
pp. 115-132
Author(s):  
Gopi Ram ◽  
Rajib Kar ◽  
Durbadal Mandal ◽  
Sakti Prasad Ghoshal
Keyword(s):  
Antenna Arrays ◽  
Excitation Amplitude ◽  
Animal Behaviour ◽  
Optimal Placement ◽  
Linear Antenna ◽  
Rf Switch ◽  
Optimal Current ◽  
Null Placement ◽  
Linear Antenna Arrays ◽  
Collective Animal Behaviour

In this paper optimal design of time modulated linear antenna arrays (TMLAA) with optimal placement of nulls in the desired direction of elevation plane has been dealt with the approach based on evolutionary algorithm like collective animal behaviour (CAB). Analysis has been done in theoretical and practical environment. Firstly the current excitation weights of the linear array of isotropic elements have been optimized by CAB is applied to improve null performance of TMLAA by Radio Frequency (RF) switch in MATLAB environment. The nulls positions of a TMLAA can be reduced significantly by optimizing the static excitation amplitudes and proper design of switch-on time intervals of each element. The CAB adjusts the current excitation amplitude of each element to place deeper nulls in the desired directions. Secondly the obtained optimal current excitation weight of the array factor is practically implemented in computer simulation technology- microwave studio (CST- MWS) environment. The array of microstrip patch antenna has been designed to operate at 5.85 GHz.

scholarly journals Challenges and solutions for studying collective animal behaviour in the wild

2018 ◽  
Vol 373 (1746) ◽  
pp. 20170005 ◽  
Author(s):  
Lacey F. Hughey ◽  
Andrew M. Hein ◽  
Ariana Strandburg-Peshkin ◽  
Frants H. Jensen
Keyword(s):  
Collective Motion ◽  
Movement Ecology ◽  
Natural World ◽  
Animal Behaviour ◽  
Natural Setting ◽  
Animal Groups ◽  
Spatial And Temporal Scales ◽  
Data Volume ◽  
In The Wild ◽  
Collective Animal Behaviour

Mobile animal groups provide some of the most compelling examples of self-organization in the natural world. While field observations of songbird flocks wheeling in the sky or anchovy schools fleeing from predators have inspired considerable interest in the mechanics of collective motion, the challenge of simultaneously monitoring multiple animals in the field has historically limited our capacity to study collective behaviour of wild animal groups with precision. However, recent technological advancements now present exciting opportunities to overcome many of these limitations. Here we review existing methods used to collect data on the movements and interactions of multiple animals in a natural setting. We then survey emerging technologies that are poised to revolutionize the study of collective animal behaviour by extending the spatial and temporal scales of inquiry, increasing data volume and quality, and expediting the post-processing of raw data. This article is part of the theme issue ‘Collective movement ecology’.

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