In contemporary dynamic automobile industry, informed decision-making is crucial for success. Accurate sales predictions are essential optimizing operations and resource allocation in the used car market. This article explores application of machine learning, specifically eXtreme Gradient Boosting(XGBoost) algorithm, predicting prices UK. The dataset consists over 110,000 data points from various brands, including features like model, year, mileage, more. Data preprocessing, outlier removal...

This paper examines the impact of introducing a green own-brand product on an e-commerce platform, incumbent competing sellers, and environment. We develop stylized model wherein seller non-green directly sell products to consumers through platform. The platform has option introduce its it within marketplace. In scenarios where no brand introduction occurs, only two incumbents compete in However, with platform’s own brand, three Our findings reveal several noteworthy results. Firstly, may...

Rationale: Extracorporeal membrane oxygenation (ECMO) technology in the field of intense care for children China has developed rapidly, and it become a key strategy rescue treatment critically ill an advanced extracorporeal life support system. Compared with adults children, neonatal respiratory disease ECMO best prognosis, average survival rate 74%. Bleeding thrombotic events during are common, morbid, potentially lethal. Therefore, how to balance coagulation state is management. Patient...

Unsupervised pre-training algorithms for graph representation learning are vulnerable to adversarial attacks, such as first-order perturbations on graphs, which will have an impact particular downstream applications. Designing effective strategy against white-box attacks remains a crucial open topic. Prior research attempts improve robustness by maximizing mutual information between the and perturbed graph, is sub-optimal because it does not adapt its defense techniques severity of attack....

During these years, rapid developments and large-scale integrations to grids of wind power posed great challenges on system annual planning its operation. If only total energy predictions are considered, existing plans will differ away real situations when some energies curtailed so that it is difficult implement the plan. In this paper, a novel method based time sequential simulation proposed. model proposed here, both characteristics load capacities peak-load regulation transmission also...

Aircraft and crew are two major resources that ensure the smooth operations of airlines. However, with anticipated growth in aviation industry, resource is predicted to be insufficient worldwide has been one bottlenecks fast-developing In addition, mismatch between aircraft influenced airlines' operation, limited full usage all resources. To resolve this problem, we propose a tactical fleet assignment pairing problem flight time allocation (TFACPP). The basic integrated model reformulated by...

Abstract The disparity map produced by matching a pair of rectified stereo images provides estimated depth information and accurate distance calculations for autonomous driving. For most networks, cost volume plays crucial role in the accuracy maps. To increase maps, an improved method called multi‐information (MICV) is proposed, with fusion concatenation correlation volume, which calculated both inner product space Euclidean space, to measure similarity between features left right images....

Cellular reconfigurable manufacturing systems (CRMS) are designed to deal with dynamic demand. This paper tries optimize cell formation decision in CRMSs alternative routing. A mixed integer nonlinear programming model is developed simultaneously formation, equipment configuration, and product mix plan. The objective maximize profit. linearization methods proposed then the solved by Gurobi. Numerical experiment sensitive analysis conducted show efficiency effectiveness of approach.

Renewable energy sources (RES) generation has huge environmental and social benefits, as a clean source with great potential. However, the difference in uncertainty characteristics of RES electric–thermal loads poses significant challenge to optimal schedule an integrated system (IES). Therefore, for different multiple uncertainties IES, this paper proposes type-II fuzzy interval chance-constrained programming (T2FICCP)-based optimization model solve above problem. In model, sets are used...

Conditional Generative Adversarial Networks (GANs) play an important role in the field of computer vision. Its strength not only lies its stronger feature extraction ability than traditional algorithms but also has achieved unprecedented success mutual game method two different neural networks. The so-called dual network GAN is called generator and discriminator. generates a picture close to expected value by inputting deep learning network. discriminator judges whether image generated true....

Abstract The improvement of the national economy has led to rapid development e-commerce business, which caused an explosive growth warehouse orders. Picking is core operation warehouse, occupies a lot time and capital costs. Therefore, optimizing picking path become urgent problem for companies solve. This article calculates distance matrix based on characteristics multi-zone warehouses, establishes Traveling Salesman Problem (TSP) model process 49 combined orders, solves through simulated...

In-line X-ray phase contrast imaging (IL-PCI) is a promising technology for clinical diagnosis because of its great advantage in distinguishing low tissues and simple structure to implement. In order recover the projections from measurements, conventional retrieval methods were developed based on assumptions such as homogeneous material, weak attenuation, thus suffered limited generalizability, practicability feasibility. Deep learning-based have been proposed success has achieved. While...