Search - ACO-AS

Search - ACO-AS - List

[Software Engineering] CAT DL : 0: Optimization problems are very important in many fields. To the present, many optimization algorithms based on computational intelligence have been proposed, such as the Genetic Algorithm, Ant Colony Optimization (ACO), and Particle Swarm
Date : 2026-01-10 Size : 925kb User : Sadaf
[Software Engineering] mayisuanfa DL : 0: 蚁群算法(ant colony optimization, ACO)，又称蚂蚁算法，是一种用来在图中寻找优化路径的机率型算法。它由Marco Dorigo于1992年在他的博士论文中提出，其灵感来源于蚂蚁在寻找食物过程中发现路径的行为-Ant colony algorithm (ant colony optimization, ACO), also known as ant algorithm, is a probabilistic algorithm used to find optimal path in the graph of the. It is composed of Marco Dorigo in his doctoral thesis in 1992 proposed, inspired by ants find food process path behavior
Date : 2026-01-10 Size : 1.58mb User : czl
[Software Engineering] Software-Quality-Prediction-Using-Cuckoo-Search-O DL : 0: this work aims to investigate the quality of software products a n important attribute of computer programs it helps to decide the degree of trustworthiness a program has in accomplishing its specific functions. This done using the Software quality model(SQMs) through the estimation of their parameters. The parameters are estimated in this work based on the available failure data and with the search techniques of Swarm Intelligence, namely, the Cuckoo Search (CS) due to its efficiency, effectiveness and robustness. A number of SQMs is studied, and the results are compared to Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and extended ACO. Results show that CS outperformed both PSO and ACO in finding better parameters-this work aims to investigate the quality of software products as an important attribute of computer programs it helps to decide the degree of trustworthiness a program has in accomplishing its specific functions. This is done using the Software quality model(SQMs) through the estimation of their parameters. The parameters are estimated in this work based on the available failure data and with the search techniques of Swarm Intelligence, namely, the Cuckoo Search (CS) due to its efficiency, effectiveness and robustness. A number of SQMs is studied, and the results are compared to Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and extended ACO. Results show that CS outperformed both PSO and ACO in finding better parameters
Date : 2026-01-10 Size : 79kb User : ankur