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市场调查报告书
商品编码
1325346

全球人工神经网络 (ANN) 市场 - 2023-2030

Global Artificial Neural Networks (ANN) Market - 2023-2030
出版日期: | 出版商: DataM Intelligence | 英文 199 Pages | 商品交期: 最快1-2个工作天内

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简介目录

市场概况

全球人工神经网络 (ANN) 市场在 2022 年达到 1.643 亿美元，预计到 2030 年将达到 6.003 亿美元，2023-2030 年预测期间复合年增长率为 17.6%。对先进技术不断增长的需求是人工神经网络（ANN）市场的主要驱动力。人工神经网络技术正在各个垂直行业中实施，例如医疗保健、银行、金融服务、保险、零售和电子商务。

在医疗保健领域，该技术用于疾病诊断、药物发现和医学成像分析，并在 COVID-19 期间显示出最快的增长。此外，在金融领域，它有助于欺诈检测、风险评估和算法交易。其他行业也受益于需求预测、客户行为分析、自动驾驶汽车等方面的 ANN 应用。

北美在人工神经网络（ANN）市场中占据主导地位，其次是亚太地区和欧洲。该增长地区先进的技术基础设施、高研发投资以及领先技术公司的存在导致该地区覆盖全球近一半的份额。

市场动态

不断进步的技术

技术的不断进步，包括硬件、软件和算法的改进，使人工神经网络解决方案更加强大和有效。例如，深度学习算法的发展使人工神经网络解决方案能够以更高的准确性和速度处理和分析更大的数据集。

此外，物联网（IoT）设备的日益普及也推动了人工神经网络市场的发展。物联网设备生成大量可用于预测分析的数据，而人工神经网络解决方案在分析这些数据以识别模式和趋势方面特别有效。此外，由于人工智能研究的不断进步、数据可用性的增加以及各个领域对智能自动化的需求，人工神经网络市场预计将继续快速增长。随着人工神经网络算法和架构的不断发展，其应用程序可能会扩展，使企业能够提取可行的见解并推动创新。

对人工智能解决方案的需求不断增加

各行业对人工智能解决方案不断增长的需求是人工神经网络市场的主要驱动力。组织正在利用人工神经网络技术开发智能係统，该系统可以分析大量数据、从模式中学习并做出准确的预测或决策。人工神经网络在预测分析、自然语言处理、图像识别和自治系统等领域都有应用。

例如，人工神经网络模型在图像和模式识别任务中表现出了非凡的成功。各行业对图像识别应用（例如面部识别、物体检测和自动驾驶）的需求正在不断增加。基于 ANN 的算法可以分析图像、检测模式并做出准确的预测，从而支持自动驾驶汽车、医学成像和製造中的质量控制等应用。

跟踪和解释困难

即使在投入大量资金后，人工神经网络解决方案仍缺乏跟踪和可解释性，这是阻碍市场发展的一个主要因素。人工神经网络解决方案可能难以理解和解释，这使得企业和组织难以信任和使用这些解决方案。

对更加透明和可解释的 ANN 解决方案的需求不断增长，特别是在医疗保健和金融等行业，基于 ANN 预测的决策可能会产生重大后果。

COVID-19 影响分析

这场大流行阻碍了人工神经网络（ANN）市场的发展，也创造了一些增长前景。例如，疫情期间向远程学习的转变以及对电信技术的日益依赖为人工神经网络的应用创造了机会。然而，疫情对全球供应链造成的破坏也影响了人工神经网络市场。硬件组件和计算基础设施的生产和交付延迟影响了 ANN 系统的部署。

目录

第 1 章：方法和范围

  • 研究方法论
  • 报告的研究目的和范围

第 2 章：定义和概述

第 3 章：执行摘要

  • 按类型分類的片段
  • 按组件分類的片段
  • 部署片段
  • 按应用程序片段
  • 最终用户的片段
  • 按地区分類的片段

第 4 章：动力学

  • 影响因素
    • 司机
      • 对预测分析的需求不断增长
      • 市场参与者的积极策略
      • 不断进步的技术
      • 对人工智能解决方案的需求不断增加
    • 限制
      • 缺乏标准化
      • 跟踪和解释困难
    • 机会
    • 影响分析

第 5 章：行业分析

  • 波特五力分析
  • 供应链分析
  • 定价分析
  • 监管分析

第 6 章：COVID-19 分析

  • COVID-19 分析
    • COVID-19 之前的情景
    • 目前的 COVID-19 情况
    • COVID-19 后或未来情景
  • COVID-19 期间的定价动态
  • 供需谱
  • 疫情期间政府与市场相关的倡议
  • 製造商战略倡议
  • 结论

第 7 章：按类型

  • 反馈人工神经网络
  • 前馈人工神经网络

第 8 章：按组件

  • 解决方案
  • 平台/API
  • 服务

第 9 章：通过部署

  • 本地
  • 云

第 10 章：按应用

  • 图像识别
  • 信号识别
  • 资料探勘
  • 其他的

第 11 章：最终用户

  • 银行、金融服务、保险
  • 零售及电子商务
  • 医疗保健和生命科学
  • 其他的

第 12 章：按地区

  • 北美
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 意大利
    • 俄罗斯
    • 欧洲其他地区
  • 南美洲
    • 巴西
    • 阿根廷
    • 南美洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳大利亚
    • 亚太其他地区
  • 中东和非洲

第13章：竞争格局

  • 竞争场景
  • 市场定位/份额分析
  • 併购分析

第 14 章：公司简介

  • Cisco Systems Inc.
    • 公司简介
    • 产品组合和描述
    • 财务概览
    • 主要进展
  • IBM Corporation
  • Microsoft Corporation
  • SAS Institute Inc.
  • Oracle Corporation
  • Splunk Inc.
  • Riverbed Technology Inc.
  • NetScout Systems Inc.
  • Ixia
  • SolarWinds Inc.

第 15 章：附录

简介目录
Product Code: ICT6542

Market Overview

Global Artificial Neural Networks (ANN) Market reached US$ 164.3 million in 2022 and is expected to reach US$ 600.3 million by 2030 growing with a CAGR of 17.6% during the forecast period 2023-2030. The rising demand for advanced technology is a major driver for the artificial neural networks (ANN) market. ANN technology is being implemented across various industry verticals such as healthcare, banking, financial services, insurance and retail and e-commerce.

In healthcare, the technology is used for disease diagnosis, drug discovery, and medical imaging analysis and has shown the fastest growth during the COVID-19 period. Furthermore, in finance, it aids in fraud detection, risk assessment, and algorithmic trading. Other sectors benefit from ANN applications in demand forecasting, customer behavior analysis, autonomous vehicles, and more.

North America holds a dominating position in the artificial neural networks (ANN) market followed by Asia-Pacific and Europe. The growing region's advanced technological infrastructure, high research and development investments, and the presence of leading technology companies lead to cover region nearly half of the share globally.

Market Dynamics

Rising Technological Advancements

Rising advancements in technology including improvements in hardware, software, and algorithms are making ANN solutions more powerful and effective. For example, the development of deep learning algorithms has enabled ANN solutions to process and analyze larger datasets with greater accuracy and speed.

Moreover, the growing popularity of Internet of Things (IoT) devices is also boosting the ANN market. IoT devices generate vast amounts of data that can be used for predictive analytics, and ANN solutions are particularly effective at analyzing this data to identify patterns and trends. Furthermore, the ANN market is expected to continue its rapid growth due to ongoing advancements in AI research, increasing data availability, and the need for intelligent automation in various sectors. As ANN algorithms and architectures continue to evolve, their applications are likely to expand, enabling businesses to extract actionable insights and drive innovation.

Increasing Demand for AI Solutions

The growing demand for AI-powered solutions across industries is a major driver of the ANN market. Organizations are leveraging ANN technology to develop intelligent systems that can analyze large volumes of data, learn from patterns, and make accurate predictions or decisions. ANN finds applications in areas such as predictive analytics, natural language processing, image recognition, and autonomous systems.

For instance, ANN models have demonstrated extraordinary success in the image and pattern recognition tasks. The demand for image recognition applications, such as facial recognition, object detection, and autonomous driving, is increasing across industries. ANN-based algorithms can analyze images, detect patterns, and make accurate predictions, enabling applications like autonomous vehicles, medical imaging, and quality control in manufacturing.

Tracking and Interpretation Difficulties

The lack of tracking and interpretability of ANN solutions even after high investments is a major factor that is hampering the market. ANN solutions can be difficult to understand and interpret, making it challenging for businesses and organizations to trust and use these solutions.

There is a growing demand for more transparent and interpretable ANN solutions, particularly in industries such as healthcare and finance, where decisions based on ANN predictions can have significant consequences.

COVID-19 Impact Analysis

The pandemic has hampered as as well created several growth prospects for the artificial neural networks (ANN) market. For instance, the shift towards remote learning and increased reliance on telecommunication technologies during the pandemic have created opportunities for ANN applications. Whereas, the disruptions caused by the pandemic in global supply chains have affected the ANN market. Delays in the production and delivery of hardware components and computing infrastructure have impacted the deployment of ANN systems.

Segment Analysis

The global artificial neural networks (ANN) market is segmented based on type, component, deployment, application, end-user and region.

Growing Demand For A Network With Great Adaptability And Learning Features

Feedback artificial neural network is expected to hold a significant share in the forecast period making it to cover more than 33.3% globally. Feedback neural networks allow for the transmission of signals in both ways. The complexity of feedback neural networks can grow quickly and they are quite powerful. Neural networks with feedback are dynamic. When such a network reaches an equilibrium point, the "state" will no longer change. Until the input changes and a new equilibrium needs to be reached, they stay at the equilibrium point.

Recurrent or interactive are other names for the architecture of a feedback neural network, but the latter is frequently used to describe feedback connections in single-layer organizations. These networks allow for feedback loops. In content addressable memories, they are employed. One of the advantages of FBANNs is their ability to adapt and learn over time. The feedback connections allow the network to adjust its connections and weights based on feedback signals, improving its accuracy and performance over time.

Geographical Analysis

Presence Of Key Players And Their Rising Investments In The Market

The presence of key players in North America is a major factor boosting the market growth of the ANN market. The companies include IBM Corporation, Microsoft Corporation, Intel Corporation, Google LLC, and Oracle Corporation, among others. These companies are investing heavily in research and development to improve the capabilities and applications of ANN. Additionally, partnerships and collaborations with other companies in the region are expected to further drive the growth of the ANN market in North America.

For instance, On November 3, 2021, Oracle Corporation announced the launch of new AI services on Oracle cloud infrastructure. Developers can train the new OCI AI services using data specific to their organizations or utilize pre-trained, out-of-the-box models on business-related data.

Competitive Landscape

The major global players in the market include IBM Corporation, Qualcomm Technologies, Inc, Intel Corporation, Oracle, nDimensional, Alyuda Research, LLC, Microsoft, SAP SE, Starmind, Afiniti, Ward Systems Group, Inc, Google LLC, NeuralWare, Microsoft.

Why Purchase the Report?

  • To visualize the global artificial neural networks (ANN) market segmentation based on type, component, deployment, application, end-user and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of artificial neural networks (ANN) market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as excel consisting of key products of all the major players.

The global artificial neural networks (ANN) market report would provide approximately 77 tables, 78 figures and 199 Pages.

Target Audience 2023

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Type
  • 3.2. Snippet by Component
  • 3.3. Snippet by Deployment
  • 3.4. Snippet by Application
  • 3.5. Snippet by End-User
  • 3.6. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Rising Demand for Predictive Analysis
      • 4.1.1.2. Aggressive Strategies From Market Players
      • 4.1.1.3. Rising Technological Advancements
      • 4.1.1.4. Increasing Demand for AI Solutions
    • 4.1.2. Restraints
      • 4.1.2.1. Lack of Standardization
      • 4.1.2.2. Tracking and Interpretation Difficulties
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Forces Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis

6. COVID-19 Analysis

  • 6.1. Analysis of COVID-19
    • 6.1.1. Before COVID-19 Scenario
    • 6.1.2. Present COVID-19 Scenario
    • 6.1.3. Post COVID-19 or Future Scenario
  • 6.2. Pricing Dynamics Amid COVID-19
  • 6.3. Demand-Supply Spectrum
  • 6.4. Government Initiatives Related to the Market During Pandemic
  • 6.5. Manufacturers Strategic Initiatives
  • 6.6. Conclusion

7. By Type

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 7.1.2. Market Attractiveness Index, By Type
  • 7.2. Feedback Artificial Neural Network *
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Feedforward Artificial Neural Network

8. By Component

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 8.1.2. Market Attractiveness Index, By Component
  • 8.2. Solutions *
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Platform/API
  • 8.4. Services

9. By Deployment

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 9.1.2. Market Attractiveness Index, By Deployment
  • 9.2. On-premises *
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Cloud

10. By Application

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.1.2. Market Attractiveness Index, By Application
  • 10.2. Image Recognition*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Signal Recognition
  • 10.4. Data Mining
  • 10.5. Others

11. By End-User

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.1.2. Market Attractiveness Index, By End-User
  • 11.2. Banking, Financial Services, Insurance*
    • 11.2.1. Introduction
    • 11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 11.3. Retail and E-commerce
  • 11.4. Healthcare and Life Sciences
  • 11.5. Others

12. By Region

  • 12.1. Introduction
    • 12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 12.1.2. Market Attractiveness Index, By Region
  • 12.2. North America
    • 12.2.1. Introduction
    • 12.2.2. Key Region-Specific Dynamics
    • 12.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 12.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 12.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 12.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 12.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 12.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 12.2.8.1. U.S.
      • 12.2.8.2. Canada
      • 12.2.8.3. Mexico
  • 12.3. Europe
    • 12.3.1. Introduction
    • 12.3.2. Key Region-Specific Dynamics
    • 12.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 12.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 12.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 12.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 12.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 12.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 12.3.8.1. Germany
      • 12.3.8.2. UK
      • 12.3.8.3. France
      • 12.3.8.4. Italy
      • 12.3.8.5. Russia
      • 12.3.8.6. Rest of Europe
  • 12.4. South America
    • 12.4.1. Introduction
    • 12.4.2. Key Region-Specific Dynamics
    • 12.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 12.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 12.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 12.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 12.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 12.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 12.4.8.1. Brazil
      • 12.4.8.2. Argentina
      • 12.4.8.3. Rest of South America
  • 12.5. Asia-Pacific
    • 12.5.1. Introduction
    • 12.5.2. Key Region-Specific Dynamics
    • 12.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 12.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 12.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 12.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 12.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 12.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 12.5.8.1. China
      • 12.5.8.2. India
      • 12.5.8.3. Japan
      • 12.5.8.4. Australia
      • 12.5.8.5. Rest of Asia-Pacific
  • 12.6. Middle East and Africa
    • 12.6.1. Introduction
    • 12.6.2. Key Region-Specific Dynamics
    • 12.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 12.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 12.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 12.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 12.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

13. Competitive Landscape

  • 13.1. Competitive Scenario
  • 13.2. Market Positioning/Share Analysis
  • 13.3. Mergers and Acquisitions Analysis

14. Company Profiles

  • 14.1. Cisco Systems Inc.*
    • 14.1.1. Company Overview
    • 14.1.2. Product Portfolio and Description
    • 14.1.3. Financial Overview
    • 14.1.4. Key Developments
  • 14.2. IBM Corporation
  • 14.3. Microsoft Corporation
  • 14.4. SAS Institute Inc.
  • 14.5. Oracle Corporation
  • 14.6. Splunk Inc.
  • 14.7. Riverbed Technology Inc.
  • 14.8. NetScout Systems Inc.
  • 14.9. Ixia
  • 14.10. SolarWinds Inc.

LIST NOT EXHAUSTIVE

15. Appendix

  • 15.1. About Us and Services
  • 15.2. Contact Us