Stroke is a cause of death and long-term disability and requires timely diagnosis and effective preventive treatment. Recent advances in machinelearning (ML) techniques have shown promising results in predicting stro...
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Personalized e-learningsystems have transformed education by personalizing learning to individual requirements & interests. This research examines how machinelearning may personalize e-learningsystems. learning...
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Effective assignment of delivery task to multiple drivers is crucial for enabling smooth operation and maximizing end-user satisfaction. This paper focuses on batch assignment, i.e., the allocation of tasks among mult...
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ISBN:
(纸本)9781643685052;9781643685045
Effective assignment of delivery task to multiple drivers is crucial for enabling smooth operation and maximizing end-user satisfaction. This paper focuses on batch assignment, i.e., the allocation of tasks among multiple drivers, starting from the same depot, while taking into account a variety of factors like load balancing delivery time, distance, workload balance, and overall effectiveness. A Kmeans Constrained technique is proposed in order to address the problem of minimizing the execution time during the assignment process and simultaneously taking into account constraints like the total number of orders, load capacity, and the number of drivers.
Changes in customer demand and technological advances increase production scheduling complexity. A solution to handle the increased complexity is to facilitate machinelearning. Current reviews of the research of sche...
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ISBN:
(纸本)9783031381645;9783031381652
Changes in customer demand and technological advances increase production scheduling complexity. A solution to handle the increased complexity is to facilitate machinelearning. Current reviews of the research of scheduling algorithms focus on summarizing existing methods. They lack the characteristics of practical implications arising from the increased complexity of the scheduling problem by Industry 4.0 and do not consider how the scheduling algorithms cope with the added complexity. Therefore, we address these issues and synthesize the current literature in a comprehensive literature review and taxonomy. We discuss how they address changeovers, buffers before and after machines, prioritization of jobs, dynamics of production, and transportation on the shop floor. Afterward, we summarize the concepts of scheduling approaches and derive five research gaps.
machinelearning and deep learning techniques are widely used in various domains to solve different problems. The prediction and recommendation type of problems exists in various domains. Due to the importance of such...
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Utilizing machinelearning (ML), a revolutionary trend in the fields of modern business and leadership, opens up new ways to improve leadership styles and propel company success. This research looks at how machine lea...
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Utilizing machinelearning (ML), a revolutionary trend in the fields of modern business and leadership, opens up new ways to improve leadership styles and propel company success. This research looks at how machinelearning techniques can be used to improve leadership strategies and the general efficiency of an organization. In the area of leadership development, this research looks at how machinelearning might be able to look at a lot of data and find trends, patterns, and insights that might not be seen with more traditional methods. In addition, it shows how important machinelearning algorithms are in predictive analytics, which helps managers see problems coming, lower risks, and take advantage of new opportunities. This research looks at how systems that use machinelearning might improve the openness, fairness, and responsibility of decision-making processes in order to build trust and teamwork. It also looks at the problems and moral issues that might come up when ML is used in leadership, emphasizing how important it is to have responsible ML governance and constant oversight to get rid of biases and make sure fair results. This research shows how machinelearning may have a big effect on leadership and the success of organizations. When leaders want to use AI-powered technology to stay ahead of the competition, boost innovation, and help their businesses grow in the digital age, our services can help.
In this paper, we study machinelearning for resource utilization and QoS performance improvement in 6G networks under α-η-μ fading and co-channel interference (CCI). We conduct extensive experiments in simulation ...
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The growing interest in health and fitness has resulted in an increase in the number of people joining fitness clubs. However, maintaining member engagement remains a challenge for fitness club operators. The goal of ...
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Crop recommendation systems based on machinelearning are becoming more and more widespread in precision agriculture. Using a variety of machinelearning algorithms, these systems select crops depending on soil type, ...
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Human emotions are essential for communication, and identifying them is critical for fields like mental health monitoring and human-computer interaction. Emotions are primarily communicated through facial expressions....
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