Biological growth is driven by numerous functions, such as hormones and mineral nutrients, and is also involved in various ecological processes. Therefore, it is necessary to accurately capture the growth trajectory of various species in ecosystems. A new sigmoidal growth (NSG) model is presented here for describing the growth of animals and plants when the assumption is that the growth rate curve is asymmetric. The NSG model was compared with four classic sigmoidal growth models, including the logistic equation, Richards, Gompertz, and ontogenetic growth models. Results indicated that all models fit well with the empirical growth data of 12 species, except the ontogenetic growth model, which only captures the growth of animals. The estimated maximum asymptotic biomass $w_{max}$ of plants from the ontogenetic growth model was not reliable. The experiment result shows that the NSG model can more precisely estimate the value and time of reaching maximum biomass when growth rate becomes close to zero near the end of growth. The NSG model contains three other parameters besides the value and time of reaching maximum biomass, and thereby, it can be difficult to assign initial values for parameterization using local optimization methods (e.g., using Gauss–Newton or Levenberg–Marquardt methods). We demonstrate the use of a differential evolution algorithm for resolving this issue efficiently. As such, the NSG model can be applied to describing the growth patterns of a variety of species and estimating the value and time of achieving maximum biomass simultaneously.

Cooperative communication is a key technology to improve the stability of UAV swarm communication. To reduce the energy consumption in cooperative communication, this study proposes a method for selecting relay nodes based on distance and energy constraints. First, a two-stage communication model was designed to explain the signal forwarding communication process. Subsequently, cluster head nodes were filtered through a competition mechanism to be used for forwarding source signals. The minimum communication capacity of the link contained the distance parameter of the relay link. Lastly, under energy and distance constraints, the optimal solution of the minimum interrupt function for the cluster head was found, and was defined as the best relay node. The experimental results show that the two parameters of network coverage and residual energy of the improved method were higher than those of other mainstream algorithms. Furthermore, the actual UAV networking test results show that the proposed relay selection method had the most residual energy. It is concluded that the relay selection method proposed in this study has good practicality and advancement in UAV cluster communication.

To solve the power allocation problem of multiple relays in cooperative communication, a sparrow improvement algorithm based on small habitats is proposed. First, the small-habitat rule increases the diversity of the energy classification of communication nodes. The problem of the premature convergence of the algorithm is solved. Subsequently, the joint jump rule is designed to replace the local search rule, and the local search rule of the sparrow algorithm is modified to avoid the local wandering phenomenon. The improved search method solves the local solution problem of the most available function. Lastly, a validation experiment of the performance of the algorithm is carried out according to the IEEE CEC 2017 benchmark document set. The simulation verifies the practicality of various algorithms. The maximum evaluation number (max FE) of the objective function is calculated to compare the performance of various algorithms. The experimental results show that the improved algorithm can increase the diversity of species. The multi-point search capability and global merit search capability are improved. Additionally, the convergence speed and computational accuracy of the algorithm are improved. The results show that the improved method is effective in controlling power in collaborative communication. The energy control algorithm has some practicality. The Friedman and Wilcoxon test criteria are applied and the convergence speed and computational accuracy of the improved algorithm are shown to be higher than those of other algorithms. This indicates that the improved power control method has some practicality in collaborative communication.