The proceedings contain 8 papers. The topics discussed include: a new niching method for the direction-based multi-objective evolutionary algorithm;two decomposition-based modern metaheuristic algorithms for multi-obj...
ISBN:
(纸本)9781467358897
The proceedings contain 8 papers. The topics discussed include: a new niching method for the direction-based multi-objective evolutionary algorithm;two decomposition-based modern metaheuristic algorithms for multi-objective optimization - a comparative study;MOPC/D: a new probability collectives algorithm for multi-objective optimization;effects of duplicated objectives in many-objective optimization problems on the search behavior of hypervolume-based evolutionary algorithms;autonomous multi-criteriadecisionmaking for route selection in a telecommunication network;sets of interacting scalarization functions in local search for multi-objective combinatorial optimization problems;a hybridization of MOEA/D with the nonlinear simplex search algorithm;and goal programming approach for multi-criteriadecision-making for an energy efficient event recognition scheme.
The proceedings contain 28 papers. The topics discussed include: Robustness Threshold Methodology for multi-criteria based Ranking using Imprecise Data;Generating Diverse and Accurate Classifier Ensembles Using multi-...
ISBN:
(纸本)9781479944682
The proceedings contain 28 papers. The topics discussed include: Robustness Threshold Methodology for multi-criteria based Ranking using Imprecise Data;Generating Diverse and Accurate Classifier Ensembles Using multi-Objective Optimization;Selection of Solutions in multi-Objective Optimization: decisionmaking and Robustness;A multi-objective Genetic Algorithm based on NSGA /I for Deriving Final Ranking from a Medium-Sized Fuzzy Outranking Relation;Clustering decision Makers with respect to similarity of views;multi-Genomic Algorithms;A Perceptual Fuzzy Neural Model;multi-criteria Approaches for Predictive Model Generation: A Comparative Experimental Study;Evaluation of E-commerce System Trustworthiness Using multi-criteria Analysis;and Nonlinear Programming Models and Method for Interval- Valued multi-objective Cooperative Games.
The proceedings contain 28 papers. The topics discussed include: using Q-learning to model bidding behavior in electricity market simulation;a low complexity evolutionary algorithm for multi-user MIMO detection;new pa...
ISBN:
(纸本)9781612840697
The proceedings contain 28 papers. The topics discussed include: using Q-learning to model bidding behavior in electricity market simulation;a low complexity evolutionary algorithm for multi-user MIMO detection;new parallel support vector regression for predicting building energy consumption;applying DPSO with dynamic diversity to books selection problem;an adaptation of the GAIA visualization method for cartography;a confidence-based recommender with adaptive diversity;integrating multi-criteria collaborative filtering and trust filtering for personalized recommender systems;evolving a non-playable character team with layered learning;decision-making on the liquefied natural gas (LNG) projects using game theory;supporting nuclear safety culture assessment using intelligent decision system;evolutionary multiobjective optimization for memory-encoding controllers in the artificial ant problem;and multi-objective optimization of cancer chemotherapy using smart PSO with decomposition.
The proceedings contain 61 papers. The topics discussed include: fuzzy multi-objective mission flight planning in unmanned aerial systems;UAV swarm mission planning and routing using multi-objective evolutionary algor...
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ISBN:
(纸本)1424407028
The proceedings contain 61 papers. The topics discussed include: fuzzy multi-objective mission flight planning in unmanned aerial systems;UAV swarm mission planning and routing using multi-objective evolutionary algorithms;tools and techniques for managing many-criteriadecision-making;modeling vague data with genetic fuzzy systems under a combination of crisp and imprecise criteria;robust basis of interval multiobjective linear and quadratic programming;multiobjective genetic algorithm for extracting subgroup discovery fuzzy rules;an interactive fuzzy satisfying method through particle swarm optimization for multiobjective nonlinear programming problems;variants of differential evolution for multi-objective optimization;and use of radial basis functions and rough sets for evolutionary multi-objective optimization.
The following topics are dealt with: computationalintelligence; multicriteriadecisionmaking; mathematical programming; fuzzy set theory; and operations research
The following topics are dealt with: computationalintelligence; multicriteriadecisionmaking; mathematical programming; fuzzy set theory; and operations research
The workshop CompSens will bring together researchers, engineers, practitioners, and students from the fields of sensor technology (ST) and computationalintelligence (CI) in order to cross-fertilize and to initiate p...
The workshop CompSens will bring together researchers, engineers, practitioners, and students from the fields of sensor technology (ST) and computationalintelligence (CI) in order to cross-fertilize and to initiate possible collaborations between these fields. ST researchers in the sensor fields will have the opportunity to enhance their CI background, and CI researchers will gain valuable feedback on the problems and the needs for “real world” applications. Sensor technology is the gate that connects computationalintelligence to the real world and understanding and awareness of ST issues is important for meaningful developments of CI. Among others, CI is also more and more used to algorithmically support the quality of ST and its outcomes. Sufficient knowledge and experience in these fields is a timely effort and there is naturally a gap between theoretical research of CI and its applications to “real-world” problems. Research in CI is often conducted by data sets that leak important aspects of real world measurement. Drift, hysteresis, calibration error, sensitivities, cross selectivity, are only a few parameters mentioned which falsify the results but does not yet get many attention in most CI algorithms. On the other side, ST researchers are going to apply more and more computationalintelligence for steadily growing multi sensor set-ups to gain a “plus” out of large sets of electronically obtained data. However, often there is still a lack in experience or knowledge of how to use and optimize the CI algorithms correctly. Mostly, algorithms get simply applied in one or the other form that a software toolbox is offering without deep analysis of the possible advantages or disadvantages of the method for a particular task. Accepted papers to ieee CompSens 2011 are works that present achievements related to the merge of sensor technology and computationalintelligence and that contribute to the cross-fertilization of the ST and CI fields.
In this talk, we will explore the intersection of connected autonomous vehicles (CAVs), edge computing, multi-agent cooperation, computer vision, and large language models (LLMs) to tackle emerging challenges in intel...
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ISBN:
(数字)9798350379365
ISBN:
(纸本)9798350379372
In this talk, we will explore the intersection of connected autonomous vehicles (CAVs), edge computing, multi-agent cooperation, computer vision, and large language models (LLMs) to tackle emerging challenges in intelligent transportation. Edge computing enables decentralized, low-latency processing, essential for real-time decision-making in tasks such as obstacle detection and navigation. multi-agent cooperation, in this context, focuses on efficient sharing of radio and computational resources, ensuring that vehicles can dynamically allocate bandwidth and processing power to maintain high performance in communication and computation-heavy environments. Computer vision technologies enable vehicles to interpret complex surroundings through advanced scene analysis, enhancing safety and decision-making. Additionally, LLMs contribute to processing large amounts of contextual data, enabling more human-like reasoning and complex decision-making. Together, these technologies offer a holistcapproach to advancing the capabilities of autonomous vehicles, creating more robust, intelligent, and sustainable transportation systems.
Feature selection is a critical preprocessing task in machine learning, particularly with high-dimensional datasets and decision-making while handling big data which presents significant challenges. This paper introdu...
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ISBN:
(数字)9798331508371
ISBN:
(纸本)9798331508388
Feature selection is a critical preprocessing task in machine learning, particularly with high-dimensional datasets and decision-making while handling big data which presents significant challenges. This paper introduces an innovative approach for multi-objective feature selection, aiming to minimize the number of features and classification error simultaneously. The method mitigates the generalization issues commonly faced when relying on the results of a single run of evolutionary algorithms. Our approach leverages the frequency of each feature across multiple runs of the optimization algorithm, applied to different portions of the data, as a key metric for ranking the features. This can reduce the risk of overfitting and enhances generalization by capturing more reliable features through repeated runs and different data subsets. To enhance the robustness of the selection, we incorporate the correlation between features and labels to determine the final feature set. To evaluate the proposed method, we selected fourteen datasets with varying numbers of features and instances. Experimental results demonstrate that this post-optimization processing technique significantly enhances generalization and consistently delivers superior performance across various datasets compared to the raw optimization results.
The proceedings contain 23 papers. The topics discussed include: autonomous market-based approach for resource allocation in a cluster-based sensor network;localization strategies for large-scale airborne deployed wir...
ISBN:
(纸本)9781424427642
The proceedings contain 23 papers. The topics discussed include: autonomous market-based approach for resource allocation in a cluster-based sensor network;localization strategies for large-scale airborne deployed wireless sensors;generalized neuron based secure media access control protocol for wireless sensor networks;using Bayesian inference for sensor management of air traffic control systems;an experimental study on agent learning for market-based sensor management;evolutionary multi-objective optimization of robustness and innovation in redundant genetic representations;fleet mix computation using evolutionary multiobjective optimization;multiobjective tuning of a multitarget tracking algorithm using an evolutionary algorithm;and on the use of informed initialization and extreme solutions sub-population in multiobjective evolutionary algorithms.
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