求解0-1背包问题的人工蜂群算法

提出了一种用于求解0-1背包问题的人工蜂群算法,详细阐述了该算法求解背包问题的具体操作过程。算法主要使用了两个思想策略:启发式贪婪算法和人工蜂群算法。通过对其它文献中仿真实例的计算和结果对比,表明该算法对求解0-1背包问题的有效性,这对人工蜂群算法解决其它离散问题会有很大帮助。     

Toward the human – Centered approach. A revised model of individual acceptance of AI

The aim of the study is to understand how humans' acceptance of Artificial Intelligences (AIs) affects human resource management (HRM). To this end, we propose an original conceptual framework based on the idea of a sustainable growth driven by the interplay between AI and HRM. Current academic debate is overly concerned by the impact that future AI will have on business and society. One of the central aspects of the conversation is whether or not AI will replace humans in value-added activities. The study remarks that humanoids are an amplificator of human potential, in light of a human-centered approach. In this vein, present work reconceptualizes the tenets of society 5.0 by considering the category of “innovation ventura”, the evolution of the innovative enterprise in the next AI landscape.     

人工神经网络及其在盲信号处理中的应用

文章讲述了人工神经网络基本知识、特点及几种典型神经网络,介绍了盲信号处理的基本概念,最后进一步指出了人工神经网络在盲信号处理中的优势。     

The role of artificial intelligence in the procurement process: State of the art and research agenda

Artificial intelligence (AI) is widely adopted in many areas, but it is still in its infancy in procurement, despite its potential. To map the state of the art of both research and practice and identify future research directions, this paper presents a mixed methodology exploratory study of the role of AI in the procurement process. The paper combines a systematic literature review, a mapping of the offerings of providers of AI-based procurement platforms and a focus group with procurement managers. Results map the functionalities of AI-based solutions throughout the procurement process, describe benefits and challenges to their adoption and identify future research directions.     

Artificial intelligence and people management: A critical assessment through the ethical lens

The dramatic increase in the use of Artificial Intelligence (AI) in workplaces around the world has tremendous potential to increase business profitability. While AI has numerous useful applications and can help speed up business processes or transform systems, its use in human resources (HR) processes and systems presents a complex series of ethical considerations that require organizational leaders to tread with caution. In this paper, we argue that as the foremost worker advocates in the firm, HR managers must be ethically sensitive and accountable. They have responsibility to carefully monitor AI programs to ensure that these systems do what they are purported to do and protect the dignity of the worker through transparency regarding the data being collected and privacy regarding its usage. Lastly, the HR manager must closely monitor the fairness and equity impacts of AI such that its use is procedurally and distributivity just.     

基于混合遗传算法的多配送中心选址问题研究

就区域配送体系的多配送中心选址问题构建确定性规划模型，相应提出混合遗传算法的求解方法。该算法结合了单亲进化遗传算法和经典遗传算法的优点，能够使部分种群择优进化的同时整体种群的解全局收敛。仿真案例表明算法能够在5％的误差限内有效、稳定的逼近全局最优解，生成的选址线路图具有实践指导价值。     

基于BP神经网络的货运量预测方法

总结了常用的几种定量预测方法,并指出其在实际应用中的不足。而人工神经网络自身具有鲁棒性、容错性、有表示任意非线性关系的能力和学习能力等特性,为预测技术提供了一种新的思想和方法。最后把这种预测方法应用于物流预测取得了满意的结果。     

基于BP神经网络的物流量预测方法研究

人工神经网络作为重要的综合评价方法,能够解决众多非线性问题,把它运用到地区货运量的预测中,可以解决因数据资料缺失,预测结果与真实结果相差较大的问题,为物流业发展提供重要的数据参考。经过实例分析证明基于神经网络的物流量预测模型是行之有效的。     

An interdisciplinary review of AI and HRM: Challenges and future directions

Artificial intelligence (AI) has the potential to change the future of human resource management (HRM). Scholars from different disciplines have contributed to the field of AI in HRM but with rather insufficient cross-fertilization, thus leading to a fragmented body of knowledge. In response, we conducted a systematic, interdisciplinary review of 184 articles to provide a comprehensive overview. We grouped prior research into four categories based on discipline: management and economics, computer science, engineering and operations, and others. The findings reveal that studies in different disciplines had different research foci and utilized different methods. While studies in the technical disciplines tended to focus on the development of AI for specific HRM functions, studies from the other disciplines tended to focus on the consequences of AI on HRM, jobs, and labor markets. Most studies in all categories were relatively weak in theoretical development. We therefore offer recommendations for interdisciplinary collaborations, propose a unified definition of AI, and provide implications for research and practice.     

人工神经网络技术在物流需求量预测中的应用

运用人工神经网络模拟人脑的思维过程,建立了多个变量之间的非线性模型,从而为准确预测物流需求量提供了科学的依据。     

财务困境预测中BP神经网络模型应用综述

金融危机席卷全球。处于金融市场之中的企业随时面,临着陷入财务困境的可能,财务困境预测模型的建立可以使公司提前预测到困境的发生,从而及早避免投资损失。随着信息技术的发展,人工神经网络预测模型开始兴起,本文重点介绍了BP神经网络模型在财务困境预测中的应用情况,并将BP神经网络模型与传统统计方法进行了比较分析。     

Unlocking the value of artificial intelligence in human resource management through AI capability framework

Artificial Intelligence (AI) is increasingly adopted within Human Resource management (HRM) due to its potential to create value for consumers, employees, and organisations. However, recent studies have found that organisations are yet to experience the anticipated benefits from AI adoption, despite investing time, effort, and resources. The existing studies in HRM have examined the applications of AI, anticipated benefits, and its impact on human workforce and organisations. The aim of this paper is to systematically review the multi-disciplinary literature stemming from International Business, Information Management, Operations Management, General Management and HRM to provide a comprehensive and objective understanding of the organisational resources required to develop AI capability in HRM. Our findings show that organisations need to look beyond technical resources, and put their emphasis on developing non-technical ones such as human skills and competencies, leadership, team co-ordination, organisational culture and innovation mindset, governance strategy, and AI-employee integration strategies, to benefit from AI adoption. Based on these findings, we contribute five research propositions to advance AI scholarship in HRM. Theoretically, we identify the organisational resources necessary to achieve business benefits by proposing the AI capability framework, integrating resource-based view and knowledge-based view theories. From a practitioner’s standpoint, our framework offers a systematic way for the managers to objectively self-assess organisational readiness and develop strategies to adopt and implement AI-enabled practices and processes in HRM.     

Me or information technology? Adoption of artificial intelligence in the delegation of personal strategic decisions

Artificial intelligence is revolutionizing the way we do business. Whereas both the adoption of technological innovations and strategic decision making have been subject to prior research, this experimental study is first to combine both. To understand the impact of choice complexity and cognitive perceptions on the willingness to delegate a strategic decision to an algorithm, we conducted an experiment with 310 participants. We find that although choice complexity has no effect, participants with low levels of situational awareness are more likely to delegate. The findings augment research on choice complexity in decision making by emphasizing the relevance of cognitive perceptions.     

基于模糊优选法的核电厂址选择外部人为事件的评价方法

出于安全考虑,核电厂在选址阶段要充分考虑厂址周围的外部人为事件。为此,我国出台了《HAF0105核电厂厂址选择的外部人为事件》,对外部人为事件进行了界定,并提出相应的勘查和评价策略。根据《事件》提出的飞机坠毁、爆炸、危险液体释放的分类,进行定量化评价,然后利用模糊优选法建立模型,将多个厂址进行比对,得到待选厂址在外部人为事件方面的优劣排序。     

浅谈如何提高造林成活率及造林质量

人工造林主要分两个时期,第一个时期为二十世纪六七十年代大规模人工造林时期,这个时期造林大部分已成林,第二个时期从2000年开始到现在,由于受立地、气侯、环境等方面影响,第二个时期所造林存在成活率低、成林困难现象。造成这种现象除自然因素外,很大程度上由人为因素造成。本文根据近年来的造林成败,提出几点造林经验,供大家参考。     

What drives a donor? A machine learning-based approach for predicting responses of nonprofit direct marketing campaigns

Direct marketing campaigns are one of the main fundraising sources for nonprofit organizations and their effectiveness is crucial for the sustainability of the organizations. The response rate of these campaigns is the result of the complex interaction between several factors, such as the theme of the campaign, the month in which the campaign is launched, the history of past donations from the potential donor, as well as several other variables. This work, applied on relevant data gathered from the World Wide Fund for Nature Italian marketing department, undertakes different data mining approaches in order to predict future donors and non-donors, thus allowing for optimization in the target selection for future campaigns, reducing its overall costs. The main challenge of this research is the presence of thoroughly imbalanced classes, given the low percentage of responses per total items sent. Different techniques that tackle this problem have been applied. Their effectiveness in avoiding a biased classification, which is normally tilted in favor of the most populated class, will be highlighted. Finally, this work shows and compares the classification results obtained with the combination of sampling techniques and Decision Trees, ensemble methods, and Artificial Neural Networks. The testing approach follows a walk-forward validation procedure, which simulates a production environment and reveals the ability to accurately classify each future campaign.     

青海省城镇聚落人工生态环境评价体系研究

城镇聚落人工生态环境是生态环境系统的一个重要组成部分。文章通过选取评价因子和权重 ,确定了青海省城镇聚落人工生态环境质量的评价指标体系。经过计算 ,得出青海省各城镇生态环境的质量评分 :省会城市西宁市生态环境质量最优 ,州地市级城镇质量由高到低依次为 :格尔木市、德令哈市、西海镇、平安镇、隆务镇、恰卜恰镇、结古镇和大武镇     

我国人造石实体面材行业发展战略思考

文章通过分析人造石实体面材行业发展的现状,对行业战略制定、战略实施方面的普遍性问题进行了探讨,提出了渐进、混合的行业发展战略模式以及若干对策建议。     

电活性聚合物薄膜大变形的力学响应分析

本文以Artificial Muscle Inc.开发的一款电活性聚合物作动器为原本,探讨了电聚合物薄膜圆环模型在受到集中力作用时的大变形问题。通过该模型变形的平衡方程和边界条件进行数值计算。结果表明,电活性聚合物薄膜的变形是非常不均匀的,这说明作为该种模型的作动器,电活性聚合物薄膜变形时材料的利用率并不高。     

人工神经网络用于短期电力负荷预测网络结构初探

目前,在电力系统短期负荷预测的手段中,已由人工预测方式逐步被软件预测方式所代替。BP人工神经网络是最常用的建立负荷预测模型的工具之一,文章对建立电力负荷BP神经网络预测模型（网络结构）进行了讨论。