This paper presents a novel adaptive multiobjective particle swarm optimization algorithm and with adaptive multi-objective particle swarm algorithm for solving objective constrained optimization problems, in which Pareto non-dominated ranking, tournament selection, crowding distance method were introduced, simultaneously the rate of crowding distance changing were integrated into the algorithm...

In order to solve the low searching efficiency in the peer-to-peer (P2P) network, introduce the ant colony algorithm with the particle swarm optimization in searching procedure. Present a new adaptive search protocol (SACASP) based on the ant colony algorithm with the particle swarm optimization in the Peer-to-Peer Network. The approach simulates the process of the ants’ searching food, and can...

Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resources and appropriate constraints. Recent developments in support vector machine and metaheuristics show many advantages of these techniques. In particular, particle swarm optimization is now widely used in solving tough ...

PSO algorithm is an intelligent optimization algorithm based on swarm intelligence. Particle swarm optimization algorithm is simple, easy to implement, and it has a wide application prospect in scientific research and engineering applications. In real life, most of the optimization problem is the optimization problem of some nonlinear discrete with the existence of local. PSO algorithm also has...

The swarm collective behaviors, such as birds flocking and fish schooling, are complex, dynamic and adaptive processes, in which the differences among individuals play an important role. As a new swarm intelligent technique, the standard particle swarm optimization only provides a simple uniform control, omitting the above mentioned phenomenon entirely. Thus, a new modified version: performance...

Given the insufficient early warning capacity of nuclear cold source biological disasters, this paper explores prediction methods for biomass caused by disasters based on deep learning. This also uses correlation analysis method to determine main environmental factors. The adaptive particle swarm optimization was used optimize depth confidence network model Gaussian continuous constrained Boltz...

This paper assumes each user has more than one queue, derives a new packet dependent proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new schemes of cross-layer packet dependent OFDM scheduling for heterogeneous classes of traffic based on proportional fairness. Scenario 1, scenario 2 and scenario 3 lea...