サンプル依頼リスト カート
  • English
  • Korean
  • Traditional Chinese
  • Simplified Chinese
デフォルト表紙
市場調査レポート
商品コード
1325346

人工ニューラルネットワーク（ANN）の世界市場-2023年～2030年

Global Artificial Neural Networks (ANN) Market - 2023-2030

出版日
ページ情報
英文 199 Pages
納期
即日から翌営業日
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=146.99円
人工ニューラルネットワーク（ANN）の世界市場-2023年～2030年
出版日: 2023年08月04日
発行: DataM Intelligence
ページ情報: 英文 199 Pages
納期: 即日から翌営業日
GIIご利用のメリット
  • 全表示
  • 概要
  • 目次
概要

市場概要

世界の人工ニューラルネットワーク（ANN）市場は、2022年に1億6,430万米ドルに達し、2023年から2030年の予測期間中に17.6%のCAGRで成長し、2030年には6億30万米ドルに達すると予測されています。先進技術に対する需要の高まりが、人工ニューラルネットワーク（ANN）市場の主な促進要因となっています。ANN技術は、医療、銀行、金融サービス、保険、小売、eコマースなど、さまざまな業界で導入されています。

医療では、この技術は疾病診断、創薬、医療画像分析に使用されており、COVID-19期間中に最も速い成長を示しています。さらに金融では、不正検知、リスク評価、アルゴリズム取引に役立っています。その他の分野では、需要予測、顧客行動分析、自律走行車などにおけるANNの活用領域から利益を得ています。

人工ニューラルネットワーク（ANN）市場では、北米が圧倒的な地位を占めており、アジア太平洋と欧州がこれに続いています。この成長地域は、高度な技術インフラ、高い研究開発投資、大手テクノロジー企業の存在により、世界シェアの半分近くを占めています。

市場力学

技術進歩の高まり

ハードウェア、ソフトウェア、アルゴリズムの改良を含む技術の進歩により、ANNソリューションはより強力で効果的なものとなっています。例えば、ディープラーニング・アルゴリズムの開発により、ANNソリューションはより大きなデータセットをより高い精度とスピードで処理・分析できるようになっています。

さらに、モノのインターネット（IoT）機器の人気の高まりもANN市場を後押ししています。IoT機器は予測分析に使用できる膨大な量のデータを生成し、ANNソリューションはこのデータを分析してパターンや動向を特定するのに特に効果的です。さらに、ANN市場は、AI研究の継続的な進歩、データの利用可能性の増加、さまざまな分野でのインテリジェントな自動化の必要性により、急成長を続けると予想されます。ANNのアルゴリズムとアーキテクチャが進化し続けるにつれて、その用途は拡大し、企業は実用的な知見を引き出し、イノベーションを推進できるようになると思われます。

AIソリューションへの需要の高まり

業界全体でAIを活用したソリューションに対する需要が高まっていることが、ANN市場の主な促進要因となっています。企業はANN技術を活用して、大量のデータを分析し、パターンから学習し、正確な予測や意思決定を行うことができるインテリジェント・システムを開発しています。ANNは、予測分析、自然言語処理、画像認識、自律システムなどの分野で応用されています。

例えば、ANNモデルは画像認識やパターン認識タスクにおいて並外れた成功を収めています。顔認識、物体検出、自動運転などの画像認識向け用途の需要は、業界全体で高まっています。ANNベースのアルゴリズムは、画像を分析し、パターンを検出し、正確な予測を行うことができるため、自動運転車、医療用画像処理、製造業における品質管理などの用途を可能にします。

追跡と解釈の難しさ

多額の投資を行ってもANNソリューションの追跡と解釈ができないことが、市場を阻害する大きな要因となっています。ANNソリューションは理解や解釈が難しく、企業や組織がこれらのソリューションを信頼し利用することを困難にしています。

特に医療や金融など、ANN予測に基づく意思決定が重大な結果をもたらす可能性のある業界では、より透明性が高く解釈しやすいANNソリューションに対する需要が高まっています。

COVID-19影響分析

パンデミックは、人工ニューラルネットワーク（ANN）市場にいくつかの成長見通しをもたらすと同時に、妨げにもなっています。例えば、パンデミックの間、遠隔学習へのシフトと通信技術への依存の高まりが、ANN用途の機会を創出しました。一方、パンデミックによる世界のサプライチェーンの混乱は、ANN市場に影響を与えています。ハードウェア・コンポーネントやコンピューティング・インフラの生産・納入の遅れは、ANNシステムの展開に影響を及ぼしています。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • 予測分析に対する需要の高まり
      • 市場参入企業の積極的戦略
      • 技術進歩の高まり
      • AIソリューションへの需要の高まり
    • 抑制要因
      • 標準化の欠如
      • 追跡と解釈の難しさ
    • 機会
    • 影響分析

第5章 産業分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制分析

第6章 COVID-19分析

第7章 タイプ別

  • フィードバック人工ニューラルネットワーク
  • フィードフォワード人工ニューラルネットワーク

第8章 コンポーネント別

  • ソリューション
  • プラットフォーム/API
  • サービス

第9章 展開方法別

  • オンプレミス
  • クラウド

第10章 用途別

  • 画像認識
  • 信号認識
  • データマイニング
  • その他

第11章 エンドユーザー別

  • 銀行、金融サービス、保険
  • 小売、eコマース
  • 医療、ライフサイエンス
  • その他

第12章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • ロシア
    • その他欧州
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他アジア太平洋
  • 中東・アフリカ

第13章 競合情勢

  • 競合シナリオ
  • 市況/シェア分析
  • M&A分析

第14章 企業プロファイル

  • Cisco Systems Inc.
    • 企業概要
    • 製品ポートフォリオと説明
    • 財務概要
    • 主な動向
  • IBM Corporation
  • Microsoft Corporation
  • SAS Institute Inc.
  • Oracle Corporation
  • Splunk Inc.
  • Riverbed Technology Inc.
  • NetScout Systems Inc.
  • Ixia
  • SolarWinds Inc.

第15章 付録

目次
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