In this work, we present a model for the phenomena of collective decision-making in social insects, using an n-dimensional system of differential equations. We perform a complete stability analysis for a special case ...
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In this work, we present a model for the phenomena of collective decision-making in social insects, using an n-dimensional system of differential equations. We perform a complete stability analysis for a special case in the model, and present numerical simulations to illustrate the behaviour of the model in the more general case. The analysis shows that up to a range of values of the parameters in the model, distinct processes of decision-making in the social insects could be modelled by the same mathematical equations. Finally, use the analysis of the mathematical model to discuss possible improvements in the performance of ant algorithms, presenting preliminary results.
This paper presents a new planner based on ant Colony Optimization for Real-coded domains (ACO(R)) for optimizing the trajectories of multiple Unmanned Aircraft Vehicles (UAVs) in Minimum Time Search (MTS) missions, w...
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ISBN:
(纸本)9781450349208
This paper presents a new planner based on ant Colony Optimization for Real-coded domains (ACO(R)) for optimizing the trajectories of multiple Unmanned Aircraft Vehicles (UAVs) in Minimum Time Search (MTS) missions, where the UAVs have to shorten the detection time of a given target while avoiding collisions and Non-Flying Zones (NFZ). Therefore, the planner has to identify the UAV trajectories that minimize the Expected Time of Target Detection (ETTD) and nullify the total of NFZ overflights and of UAV collisions. To achieve it, the planner is backed by an ACO(R) that 1) ensures the feasibility of the trajectories by encoding them as a sequence of input UAV control commands and by decoding them through complex UAVs kinematic/dynamic models, 2) handles the uncertainty of the sensor and of the target location in the computation of the ETTD using Bayesian theory, and 3) improves the planning process with a heuristic that has been especially designed to exploit the probability and spatial properties of the problem. All these properties let our ACO(R) based planner handle successfully minimum time target detection missions in real world scenarios, as the results analyzed in this paper, obtained over different setups, show.
Tato diplomová práce se zabývá plánováním cesty robotu. Obsahuje přehled obecných přístupů pro plánování cesty. Dále popisuje metody rojové intelig...
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Tato diplomová práce se zabývá plánováním cesty robotu. Obsahuje přehled obecných přístupů pro plánování cesty. Dále popisuje metody rojové inteligence a jejich aplikace na plánování cesty robotu. Práce obsahuje návrhy změn pro mravenčí algoritmy a prezentuje výsledky experiment provedených pomocí implementovaných algoritmů.
Enterprises plan detailed evaluation of only those engineering change (EC) effects that might have a significant impact. Using past EC knowledge can prove effective in determining whether a proposed EC effect has sign...
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Enterprises plan detailed evaluation of only those engineering change (EC) effects that might have a significant impact. Using past EC knowledge can prove effective in determining whether a proposed EC effect has significant impact. In order to utilize past EC knowledge, it is essential to identify important attributes that should be compared to compute similarity between ECs. This paper presents a knowledge-based approach for determining important EC attributes that should be compared to retrieve similar past ECs so that the impact of proposed EC effect can be evaluated. The problem of determining important EC attributes is formulated as the multi-objective optimization problem. Measures are defined to quantify importance of an attribute set. The knowledge in change database and the domain rules among attribute values are combined for computing the measures. An ant colony optimization (ACO)-based search approach is used for efficiently locating the set of important attributes. An example EC knowledge-base is created and used for evaluating the measures and the overall approach. The evaluation results show that our measures perform better than state-of-the-art evaluation criteria. Our overall approach is evaluated based on manual observations. The results show that our approach correctly evaluates the value of proposed change impact with a success rate of 83.33%.
Airborne highly dynamic ad hoc UAV network has features of high node mobility, fast changing network topology, and complex application environment. The performance of traditional routing algorithms is so poor over asp...
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Airborne highly dynamic ad hoc UAV network has features of high node mobility, fast changing network topology, and complex application environment. The performance of traditional routing algorithms is so poor over aspects such as end to end delay, data packet delivery ratio, and routing overhead that they cannot provide efficient communication formulti-UAVs carrying out missions synergistically. A bionic optimization based stability and congestion aware routing algorithm-BSCAR algorithm-is proposed to solve these problems. This algorithm integrates biological behavior and dynamic source routing algorithm, which can sense the congestion level of routes and the stability of routes. ant colony optimization algorithm and the mathematical model of Physarum's behavior exert effort in the process of route discovery and maintenance. The level of pheromone in routes is chosen as a standard to choose route and calculated by the mathematical model of Physarum's behavior. A new volatilization mechanism of pheromone is also introduced into the algorithm. Meanwhile, the algorithm can make adjustment to the variance of UAV formation to prevent the compromise of the network performance. The simulation results show that the BSCAR algorithm has superiority over traditional algorithms and it is dependable in battlefield environment.
The light weight aggregate is an aggregate that weighs less than the usual rock aggregate and the quarry dust is a rock particle used in the concrete for the experimentation. The significant intention of the proposed ...
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The light weight aggregate is an aggregate that weighs less than the usual rock aggregate and the quarry dust is a rock particle used in the concrete for the experimentation. The significant intention of the proposed technique is to frame a mathematical modeling with the aid of the optimization techniques. The mathematical modeling is done by minimizing the cost and time consumed in the case of extension of the real time experiment. The proposed mathematical modeling is utilized to predict four output parameters such as compressive strength (Mpa), split tensile strength (Mpa), flexural strength (Mpa), and deflection (in mm). Here, the modeling is carried out with three different optimization techniques like genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) with 80% of data from experiment utilized for the training and the remaining 20% for the validation. Finally, while testing, the error value is minimized and the performance obtained in the ACO for the parameters such as compressive strength, split tensile strength, flexural strength, and deflection is 91%, 98%, 87%, and 94% of predicted values, respectively, in the mathematical modeling.
Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which t...
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Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution.
Digital technology has brought drastic changes to the design methods, values, and design tools of neighbourhood public spaces, thereby changing the behavioural patterns of people in neighbourhood public spaces. Theref...
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Digital technology has brought drastic changes to the design methods, values, and design tools of neighbourhood public spaces, thereby changing the behavioural patterns of people in neighbourhood public spaces. Therefore, people's requirements for urban public space have changed and are characterised by high efficiency, high precision, humanization, and high aesthetics. Scholars at home and abroad have conducted many studies and practises on the application of digital technology to neighbourhood design, but there is a lack of systematic research practises on the use and analysis of multi-faceted data. This paper selects the Xiaomi Beijing Changping II design project, simulates and deduces the physical environment of its location, simulates the results of the natural environment by using the data of sunshine, wind, and water catchment in the physical environment, and then simulates the crowd's action paths by combining kinetic algorithms and ant algorithms to optimise the design methods, processes, and results of the neighbourhood public space on the basis of this research. The research team designed five groups of programmes for the project based on different design methods and processes, and conducted a comparative study of the five groups of programmes through the hierarchical analysis method in conjunction with the fuzzy comprehensive evaluation method, as well as discussing them in conjunction with the actual bidding results of the project and the scoring conclusions of the industry experts. The results of the study show that the design scheme for neighbourhood public space based on physical environment simulation and crowd simulation is better able to take advantage of the analytical and predictive advantages of the technology and unite with the designer's aesthetic interests, balancing the data objectivity and aesthetic subjectivity in the design process. The method is more likely to achieve a design solution that combines systematicity, foresight, rationality
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