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市場調查報告書
商品編碼
1325346

全球人工神經網路 (ANN) 市場 - 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: 約2個工作天內

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簡介目錄

市場概況

全球人工神經網路 (ANN) 市場在 2022 年達到 1.643 億美元，預計到 2030 年將達到 6.003 億美元，2023-2030 年預測期間年複合成長率為 17.6%。對先進技術不斷成長的需求是人工神經網路（ANN）市場的主要驅動力。人工神經網路技術正在各個垂直行業中實施，例如醫療保健、銀行、金融服務、保險、零售和電子商務。

在醫療保健領域，該技術用於疾病診斷、藥物發現和醫學成像分析，並在 COVID-19 期間顯示出最快的成長。此外，在金融領域，它有助於欺詐檢測、風險評估和算法交易。其他行業也受益於需求預測、客戶行為分析、自動駕駛汽車等方面的 ANN 應用。

北美在人工神經網路（ANN）市場中佔據主導地位，其次是亞太地區和歐洲。該成長地區先進的技術基礎設施、高研發投資以及領先技術公司的存在導致該地區覆蓋全球近一半的佔有率。

市場動態

不斷進步的技術

技術的不斷進步，包括硬體、軟體和算法的改進，使人工神經網路解決方案更加強大和有效。例如，深度學習算法的發展使人工神經網路解決方案能夠以更高的準確性和速度處理和分析更大的資料集。

此外，物聯網（IoT）設備的日益普及也推動了人工神經網路市場的發展。物聯網設備生成大量可用於預測分析的數據，而人工神經網路解決方案在分析這些數據以識別模式和趨勢方面特別有效。此外，由於人工智慧研究的不斷進步、數據可用性的增加以及各個領域對智慧自動化的需求，人工神經網路市場預計將繼續快速成長。隨著人工神經網路算法和架構的不斷發展，其應用程式可能會擴展，使企業能夠提取可行的見解並推動創新。

對人工智慧解決方案的需求不斷增加

各行業對人工智慧解決方案不斷成長的需求是人工神經網路市場的主要驅動力。組織正在利用人工神經網路技術開發智慧系統，該系統可以分析大量數據、從模式中學習並做出準確的預測或決策。人工神經網路在預測分析、自然語言處理、圖像識別和自治系統等領域都有應用。

例如，人工神經網路模型在圖像和模式識別任務中表現出了非凡的成功。各行業對圖像識別應用（例如臉部辨識、物體檢測和自動駕駛）的需求正在不斷增加。基於 ANN 的算法可以分析圖像、檢測模式並做出準確的預測，從而支持自動駕駛汽車、醫學成像和製造中的品質控制等應用。

追踪和解釋困難

即使在投入大量資金後，人工神經網路解決方案仍缺乏追踪和可解釋性，這是阻礙市場發展的一個主要因素。人工神經網路解決方案可能難以理解和解釋，這使得企業和組織難以信任和使用這些解決方案。

對更加透明和可解釋的 ANN 解決方案的需求不斷成長，特別是在醫療保健和金融等行業，基於 ANN 預測的決策可能會產生重大後果。

COVID-19 影響分析

這場大流行阻礙了人工神經網路（ANN）市場的發展，也創造了一些成長前景。例如，疫情期間向遠程學習的轉變以及對電信技術的日益依賴為人工神經網路的應用創造了機會。然而，疫情對全球供應鏈造成的破壞也影響了人工神經網路市場。硬體組件和計算基礎設施的生產和交付延遲影響了 ANN 系統的部署。

目錄

第 1 章：方法和範圍

  • 研究方法論
  • 報告的研究目的和範圍

第 2 章：定義和概述

第 3 章：執行摘要

  • 按類型分類
  • 按組件分類
  • 部署片段
  • 按應用程式片段
  • 最終用戶的片段
  • 按地區分類

第 4 章：動力學

  • 影響因素
    • 司機
      • 對預測分析的需求不斷成長
      • 市場參與者的積極策略
      • 不斷進步的技術
      • 對人工智慧解決方案的需求不斷增加
    • 限制
      • 缺乏標準化
      • 追踪和解釋困難
    • 機會
    • 影響分析

第 5 章：行業分析

  • 波特五力分析
  • 供應鏈分析
  • 定價分析
  • 監管分析

第 6 章：COVID-19 分析

  • COVID-19 分析
    • COVID-19 之前的情景
    • 目前的 COVID-19 情況
    • COVID-19 後或未來情景
  • COVID-19 期間的定價動態
  • 供需譜
  • 疫情期間政府與市場相關的舉措
  • 製造商戰略舉措
  • 結論

第 7 章：按類型

  • 反饋人工神經網路
  • 前饋人工神經網路

第 8 章：按組件

  • 解決方案
  • 平台/API
  • 服務

第 9 章：通過部署

  • 本地
  • 雲

第 10 章：按應用

  • 圖像識別
  • 訊號識別
  • 數據挖掘
  • 其他

第 11 章：最終用戶

  • 銀行、金融服務、保險
  • 零售及電子商務
  • 醫療保健和生命科學
  • 其他

第 12 章：按地區

  • 北美
    • 我們
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 俄羅斯
    • 歐洲其他地區
  • 南美洲
    • 巴西
    • 阿根廷
    • 南美洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳大利亞
    • 亞太其他地區
  • 中東和非洲

第13章：競爭格局

  • 競爭場景
  • 市場定位/佔有率分析
  • 併購分析

第 14 章：公司簡介

  • Cisco Systems Inc.
    • 公司簡介
    • 產品組合和描述
    • 財務概覽
    • 主要進展
  • IBM Corporation
  • Microsoft Corporation
  • SAS Institute Inc.
  • Oracle Corporation
  • Splunk Inc.
  • Riverbed Technology Inc.
  • NetScout Systems Inc.
  • Ixia
  • SolarWinds Inc.

第 15 章：附錄

簡介目錄
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