Bill Porto


B.A.    Applied Mathematics, University of California at San Diego

M.A.    Applied Mathematics, UCSD 

Experience Summary

Mr. Porto is President of Natural Selection, Inc., and has been with the firm since September, 1995. Prior to joining Natural Selection, Inc., Mr. Porto was a Senior Principal Engineer with ORINCON Corporation (1981-1995), and has been actively involved in signal and information processing algorithm, analysis, and software development for over 20 years. These efforts have been in the areas of unmanned systems course of action (COA) planning, pattern classification/recognition, multi-hypothesis Bayesian target tracking, multi-sensor correlation, optimal estimation, acoustic, electromagnetic, and geoseismic wave propagation and analysis, and signal/image processing. In addition he is a recognized expert on neural networks, and has presented tutorials on neural networks at numerous conferences. He has headed the Office of Naval Technology (ONT) advisory panel on neural networks and data fusion since 1990. 

Mr. Porto has extensive experience combining signal/image processing, fuzzy logic, neural networks and evolutionary computation in the use of acoustic, seismic and electromagnetic signals for detection, classification, and tracking. His studies and software engineering efforts in these fields have been presented in journal articles, at professional meetings, and in numerous technical reports. 

He has been responsible for technical management and execution on corporate projects including efforts in UAV control, optimal COA planning, factory scheduling, material utilization and allocation, urban traffic control, and signal and image processing, particularly relying on the use of evolutionary algorithms. Mr. Porto holds a B.S. in applied mathematics from UCSD and M.A. in applied mathematics (UCSD). He was a Co-Chair of the 1989 IEEE International Joint Conference on Neural Networks and was the General Chair of Evolutionary Programming VII: The Seventh Annual Conference on Evolutionary Programming, held in San Diego in 1998. He is a charter officer of the Evolutionary Programming Society and has been an Associate Editor of the IEEE Transactions on Evolutionary Computation since its inception in 1997. He has also assisted in the organization of other IEEE conferences including IEEE Conferences on Neural Networks (IJCNN), IEEE Conferences on Evolutionary Computation (CEC), and IEEE Ocean Engineering Society and Marine Technology Society conferences (OCEANS), from 1995-present. Mr. Porto has served as the Information Processing Technology Chair for IEEE OES and MTS since 1992.

Experience History


Natural Selection – Exec. Vice President


2007 - present – Automated Optimal Workorder Scheduling System for Global Delivery Tech: Mr. Porto is leading the design and implementation of automated scheduling software for commercial service industries. A service-oriented application (SOA) software architecture is used together with an evolutionary scheduler to optimally assign work order tasks with respect to a service company’s operational objectives and constraints. As a side benefit it will also significantly reduce call center operation costs.


2006 - present – UGS Sensor System for Textron Systems: Mr. Porto is researching the application of evolutionary agent-based systems to optimize sensor resource allocations within Textron’s Terrain Commander (TC2), the latest version of Textron’s Unattended Ground Sensor (UGS) product line, developed for the US Army under the Hornet Wide Area Munitions and Air Deliverable Acoustic Sensor (ADAS) programs. This software system will be implemented in the form of a plug-in scenario evaluator wherein the physical location, movements, and mixture of unattended ground sensors can be optimized dynamically with respect to topography and platform (e.g., OPFOR) movements.


2004-2006 – J-UCAS Sensor Analysis/Optimization for Northrop Grumman Electronic Systems: Mr. Porto lead the development of a SSSC mission planning tool that allows rapid tradeoff analyses of various sensor systems proposed for the J-UCAS X-47 platform and subsequent UCAS variants. This system incorporates both general situational awareness and contact dependent aspects to allow specification of surveillance and reconnaissance missions. The prototype software developed under this program will demonstrate the capability of operating one or more AUVs as remote sensing systems that can automatically search for, prosecute, and communicate information on targets of interest in dynamic at-sea environments. This prototype software is slated for transition to an on-board operational system scheduled for a demonstration within a UCAS testbed in the 2007 timeframe.


2003-2007 – Autonomous Mission Planning for Distributed AUV Assets: Mr. Porto lead the development of evolutionary algorithms to generate courses of action (COAs) for unmanned aerial vehicles for AFRL, Rome, N.Y. The parallel-processing software developed under this program will demonstrate the cooperative and collaborative capabilities of multiple AUVs in realistic simulations. Preliminary software demonstrations conducted at the SOCOM TNT experiments at Camp Roberts, CA proved the efficacy of these techniques for real-time COA planning for small UAVs. This software has formed the basis for an integrated UAV control system under investigation by the UAV Battlelab in Nevada.


2003-2005 – Tomahawk Strike Network (TSN) Analysis: Mr. Porto investigated the use of computational intelligence techniques to recognize and classify information patterns in electromagnetic transmissions intercepted from TSN satellite data link transmissions (SATCOM). This project, under the direction of Johns Hopkins University’s Applied Physics Lab (JHU/APL) and NAVAIR, assessed the vulnerability of the TSN system with respect to these intercepts, demonstrated state-of-the-art techniques that could be used to compromise the system, and provided recommendations for reducing the capability of outside interests to exploit this information.


2003-2004 – Northrop Grumman UCAR Evolutionary Mission Manager (EMM):  Mr. Porto lead the research and development of prototype autonomous UAV mission manager software for Northrop-Grumman’s UCAR effort. This joint DARPA/Army project developed mission planning software for the Unmanned Combat Aerial Rotorcraft (UCAR) program. The software generates COAs, and dynamically adapts these task plans based upon both sensed information and data from outside intel sources.


1999-2004 – Cruise Missile Strike and Route Planning: Mr. Porto developed novel algorithms using evolutionary computation techniques to automate cruise missile strike planning for NAVAIR. This system, which interfaces with the ComGlobal mission planning software, generates optimal strike plan solutions in near-real time. Mr. Porto lead the design and implementation efforts of all C/C++ software developed for this project.


1998-2003 – Determination of RNA Secondary Structure: Mr. Porto designed and implemented novel software for ISIS Corporation that uses evolutionary algorithms to determine the secondary folding structure of RNA. This effort, potentially a first in the pharmaceutical industry, discovers and classifies homologous structures conserved through the process of natural evolution. The software has been successfully tested on a number of RNA structures, and significantly outperforms conventional industry techniques, both in quality of solutions as well in computational time.


1999-2002 – U.S. Army Evolution of Intelligent Behaviors:  Mr. Porto was responsible for the development of software which extends the previous work for STRICOM to incorporate multiple personnel soft-factors using JANUS as a simulation engine. This approach uses distributed processing techniques to provide true real-time evolution of tactical plans for unmanned ground vehicles. Mr. Porto was the project manager and chief architect for this U.S. Army and National Guard training program.


1998-2002 – Evolving Interactively Intelligent Adversaries: Mr. Porto modified and extended the automated behavior planning system designed for STRICOM to work on a heterogeneous suite of computers for the U.S. Army at Ft. Leavenworth, Kansas. Mr. Porto was the principal investigator and software development manager for this project. Modifications and extensions to the previous STRICOM work include the creation of robust communication mechanisms, object-oriented design, advanced prediction algorithms, terrain features, and extension of the previous system to utilize multi-player game theory. This project was managed in conjunction with UCSD personnel in a joint STTR effort.

1998-2000 – Classification of Seismic Signals: In support of the DARPA MEMs project, Mr. Porto designed and implemented a novel neural-network based system to classify a range of seismic signals. Features from these signals, first extracted using advanced signal processing techniques, range from a single marine walking to various vehicle types. The classification algorithm uses evolutionary computation to design and train the networks. This system was tested with great success in the field at Camp Pendleton, California, and greatly enhances the classification capabilities over the current CFAR outputs.


1997-1998 – Optimal Allocation of Satellite/UAV Surveillance Resources: Mr. Porto developed software for Rockwell/Boeing Corp. that optimally allocates satellite and unmanned aerial vehicle as used in surveillance settings. This software uses evolutionary techniques to temporally allocate these resources while maintaining a complex set of constraints (slew times, image qualities, differential- time imaging, etc.). This software outperformed the heuristic and human methods previously used to allocate these resources. It also generates optimal solutions for combined UAV and satellite resources that previously were done separately.


1995-2003 – Automated Cruise Missile Strike Planner: Mr. Porto worked with JHU/APL to develop and integrate evolutionary algorithms that optimize strike plans for cruise missiles. Various design aspects included multiple missile types, automatic environmental updates, temporal decision planning, coordination with communication schedules, and complex constraint satisfaction. The software is being used in-situ at JHU/APL and has been demonstrated to NAVAIR and at various naval facilities. Mr. Porto was responsible for the design and implementation efforts of all C/C++ software developed for this project.


1996-1997 – Evolving Interactively Intelligent Agents: Mr. Porto designed and implemented an automated system that generates interactively intelligent behaviors for computer-generated forces for the U.S. Army at STRICOM. These behaviors interact with other computer or human-guided forces, and learn appropriate actions in light of a constantly changing environment. He has also adapted this software for path planning and robotic planning for NIST.


1995-1998 – Assyst, GmbH: Mr. Porto designed, implemented, and integrated an automated marker template (material utilization) optimization package for Assyst. The software programs optimized the allocation of template markers for garment cutting using evolutionary computation. Software developed for this project outperformed both human and other optimization methods, and is currently in use at numerous Levi Strauss cutting plants throughout the world.


1995-1996 Levi Strauss: Mr. Porto designed an automated factory scheduling for Levi Strauss finishing plants. This system uses evolutionary programming to optimize the temporal allocation of various garments to a set of processing machines (dechlorinate, stone wash, rewash, dry, etc.) in the finishing plant. This software was tested on site at the finishing plant at Amarillo Texas, and is currently being used to evaluate throughput for operations at several other Levi Strauss finishing plants.


ORINCON – Senior Principal Engineer

1991-1995 - Nonacoustic ASW Studies for the Office of Naval Research:  Mr. Porto studied and developed conventional and neural network algorithms for non-acoustic ASW utilizing magnetic, thermal, and other sensors. This work includes modeling as well as real data acquisition and analysis for surface and subsurface target detection, classification, and tracking in shallow water. This project involves sensor development, data processing, neural network/conventional algorithmic designs, data fusion with other sensor types, and tactical utilities studies. Mr. Porto was task manager of the NN/Data Fusion research and is also a member of the ONR Nonacoustic ASW Advisory Panel.


1988-1995 - DARPA Acoustic Nontraditional Exploitation System (DANTES): Mr. Porto’s work on the DARPA sponsored DANTES program has included developing advanced real-time broadband signal processing methods to extract and enhance acoustic data features for input into successfully implemented methods and neural network topologies that deal with a wide variety of passive nontraditional signals.  Mr. Porto has participated in numerous at-sea experiments onboard USN submarines gathering and processing data in real-time. He has developed novel electronic circuits that modify existing commercial VCR recording systems for storage of high bandwidth multi-channel PCM data. He has also developed novel neural network methods to deal with active acoustic returns from CTFM sonars for mine detection. This work involved the construction of special control circuitry, processing software, and detection algorithms. Mr. Porto also developed real-time software and hardware for the multichannel PRISM signal processing and pattern classification system.


1988-1993 – Artificial Intelligence-Based Sonar Signal Processing for the Automated Surveillance Information Processing System (ASIPS): Mr. Porto performed system software development on Sun workstations and MicroVAXs for the ASIPS program to develop a target detection, classification, and tracking system that employs artificial intelligence techniques and neural networks. He adapted the advanced neural net approaches to narrowband, broadband, and transient signal processing that he developed under the Air Defense Initiative program described below to use both passive and active acoustic data sources, including returns from CTFM, monostatic, and bistatic active sonar sources. Information from these various sources is processed, then fused by an expert system to generate higher level, higher accuracy scenarios used in navigation and threat assessment. This program automated many of the IUSS detection, classification, and tracking functions that were currently operator intensive.


1990 – Multi-Static Sonar (MSS) Program:  Mr. Porto supported the design, development, and testing of real-time data driven software for the MSS program.  This work included design and implementation of sequential detectors, Kalman filter trackers, and system communications software. This software, programmed in C and executed on a Sun computer, is being used in sea trials on the LFA/MSS platform in real time under full Navy operations tests.


1987-1990 – Air Defense Initiative (ADI) Submarine Signal Detection and Analysis: Mr. Porto supported the ADI Signal Detection and Analysis Program for the Naval Ocean Systems Center (NOSC). He was responsible for the development and application of broadband acoustic signal processing algorithms, optimal matched filters, and graphics software. He researched neural network approaches to the detection and classification of nontraditional acoustic signals in real time and successfully implemented software simulating neural networks that process real data.


1986-1987 – PICES-Software Engineering and Analysis:  Mr. Porto was heavily involved in the analysis of system requirements and the development of the Bayesian Recursion (BAYR)-derived PICES multitarget, multisensor data fusion/correlation algorithm for NOSC. This work included adaptation of the BAYR code to utilize array processors, parallel processing and database management techniques, and design and analysis of extended Kalman Filter trackers within this code. He analyzed system performance and created measures of performance and effectiveness (MOEs and MOPs) to measure and quantify algorithmic throughput and efficiency.


1984-1986 – JTIDS Support and Analysis:  For the NOSC Joint Tactical Information Distribution System (JTIDS) development section, Mr. Porto performed research and analysis of various aspects of optimal RELNAV filtering, algorithm design, communications signal transmission, and wave propagation nonlinearities. This included modeling and generating a computer simulation of the JTIDS system (SCENEVAL) to develop and test RELNAV Kalman filter designs and optimize communications system performance.  The code was designed, fully documented (PDS, PPS) and written to NAVY MIL-STD 1679 and is currently installed in the JTIDS JDES testbed at NOSC.  He designed specific system test and evaluation plans for Naval requirements of the JTIDS RELNAV function. Mr. Porto also wrote several technical documents for this project.


1983-1985 – Undersea Noise Studies and Analysis:  For the SURTASS and IUSS systems, Mr. Porto was involved in the analysis of undersea noise data.  This included analyzing the statistical properties of ambient ocean noise, departures from Gaussianity, and the development of revised ocean noise models based on these studies. Mr. Porto developed special microprocessor-based signal processing algorithms to correlate and filter the undersea background noise data.


1981-1984 – STIC Experiment Support:  Mr. Porto was actively involved in numerous real-time multitarget tracking experiments at the Acoustic Research Center (now Surveillance Test and Integration Center (STIC)) at the Naval Ocean Systems Center (NOSC). This work involved developing FORTRAN-based Kalman filter tracking algorithms and surveillance displays for these experiments.  Undersea data from multiple sources and radar data were combined using data fusion techniques developed at ORINCON. He is thoroughly familiar with the ARC computer center and its peripheral devices.


1981-1983 – Ocean Tactical Targeting: Mr. Porto was responsible for the analysis of system requirements and coding of joint detection/estimation search and Kalman filter tracking algorithms for a multitarget, multisensor surveillance system. He modified and implemented a numerical partial differential equation-solving package to simulate multidimensional probability density functions that describe these sensor-target scenarios. He also developed various programs using adaptive and Kalman filters to optimize multisensor trajectory search paths using both positive and negative information from these same sensors. Mr. Porto has developed numerous graphic display packages designed to display two- and three-dimensional data for multitarget, multisensor systems, tracking systems and various signal processing applications. He is thoroughly familiar with numerical analysis techniques, covariance analysis and optimal filter design, and he has developed new high precision, fast multidimensional function optimization algorithms. This work required processing and analysis of data collected from air, surface, and subsurface Navy platforms.


Del Mar Technical Associates – Engineering Analyst

1980-1981 – Geoseismic Wave Propagation Modeling: Mr. Porto was involved in the development of a computer program to simulate and model geoseismic wave propagation and strong ground-motion phenomena. This required research and development of numerically stable and efficient routines to calculate Greens Functions for heterogeneous three-dimensional earth models. He developed and implemented various multistage signal processing techniques for deconvolving the ground motion records to determine site-specific impulse functions. The software was used to simulate ground motion frequency spectra for the San Onofre and Diablo Canyon nuclear power plant sites, and results were presented in testimony at the NRC licensing hearings.


UCSD - Teaching Assistant

1979-1981 – Mathematics Department:  Mr. Porto was a teaching assistant for Professor John A. Trangenstein; in Calculus, Linear Algebra, Numerical Analysis, and Differential Equations.


1981-1983 – Electrical Engineering Department:  Mr. Porto was a teaching assistant for Dr. Vivek Samant; in Non-Linear Optimization.


Grossmont Community College – Tutor

1977-1980 – Math and Statistics Tutor:  Mr. Porto tutored college students in all levels of mathematics and statistics at the Learning Resources Center.


Security Clearance

Mr. Porto was granted a (current) TOP SECRET clearance by DISCO on 2 August 1984.




Oceans'99                    Sept. 13, 1999 "Computational Intelligence: Theory and

Seattle, Washington                            Applications in Ocean Surveillance"


ANNIE'97                  Nov. 9, 1997   "An Introduction to Evolutionary Computation"

St. Louis, Missouri


Supercomputing'95     Dec. 4, 1995    "Genetic Algorithms and

San Diego, California                         Evolutionary Programming"


Oceans'95                    Oct. 12, 1995  "Computational Intelligence: Theory and

San Diego, California                         Applications in Ocean Surveillance"              


Oceans'93                    Oct. 18, 1993  "Ocean Engineering Applications of Neural

Victoria, B.C., Canada                       Networks and Fuzzy Systems"


Oceans'92                    Oct. 26, 1992  "Neural Networks: Theory and Ocean

Newport, Rhode Island                      Surveillance Applications"





V.W. Porto, 2005, " Tomahawk Strike Network (TSN) SATCOM Analysis and Vulnerability Assessment", Final Report for NAVAIR, JHU/APL, January 2005. (classified)


Porto VW, Fogel DB, Fogel LJ, Fogel GB, Johnson N, and Cheung M (2005) “Classifying Sonar Returns for the Presence of Mines: Evolving Neural Networks and Evolving Rules,” 2005 IEEE Symposium on Computational Intelligence for Homeland Security and Personal Safety, D.B. Fogel and V. Piuri (eds.), IEEE Press, Piscataway, NJ, pp. 123-130.


Porto VW, Fogel LJ, and Fogel DB (2004) “Using Evolutionary Computation for Seismic Signal Processing: A Homeland Security Application,” Proceedings of 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, IEEE Press, Venice, Italy, pp. 62-66.


Fogel GB, Porto VW, Weekes DG, Fogel DB, Griffey RH, McNeil JA, Lesnik E, Ecker D, and Sampath R (2002) “Discovery of RNA Structural Elements Using Evolutionary Computation,” Nucleic Acids Research, Vol. 30:23, pp. 5310-5317.


Porto, V.W., (2000) “Evolutionary Programming.” In Evolutionary Computation 1: Basic Algorithms and Operators, T. Back, D. Fogel, T. Michalewicz (Eds), IOP Publishing.


V. William Porto, 1999, " Using Evolutionary Programming to Optimize the Allocation of Surveillance Assets", Simulated Evolution and Learning, B. McKay, X. Yao, C.S. Newton, J.-H. Kim, T. Furuhashi (Eds.), Springer Verlag, LNAI, Volume 1585, Issue , pp 0215-0222.


V.William Porto, David B. Fogel, and Lawrence J. Fogel 1998, "Generating Novel Tactics through Evolutionary Computation ", SIGART Bulletin, Fall 1998, ACM Press, Vol 9, No. 2, pp. 8-14.


V. William Porto, 1998, "Evolving Integrated Low-Level Behaviors into Intelligently Interactive Simulated Forces", Evolutionary Programming VII, 7th Annual Conference on Evolutionary Programming, V.W. Porto, N. Saravanan, D. Waagen, and A.E. Eiben, eds., San Diego, CA, Berlin, Germany: Springer Verlag, pp. 781-791.


V. William Porto, 1997, "Evolution of Intelligently Interactive Behaviors for Simulated Forces", Evolutionary Programming VI, 6th International Conference, EP97, Peter J. Angeline, Robert G. Reynolds, John R. McDonnell, and Russ Eberhart, eds., Berlin, Germany: Springer Verlag, pp. 419-429.


V. William Porto, 1997, "On the Practical Application of Evolutionary Programming to Optimize Job Shop Scheduling", IPMM'97: Australiasia-Pacific Forum on Intelligent Processing & Manufacturing of Materials, T. Chandra, S.R. Leclair, J.A. Meech, B. Verma, M. Smith, B.Balachandran, eds., Brisbane, Australia: Watson Ferguson & Co., Vol. 1, pp. 593-599.


V. William Porto, "Evolutionary Programming", 1997, in Handbook of Evolutionary Computation, T. Back, D.B. Fogel, Z. Michalewicz eds., Oxford, U.K.: IOP Press and Oxford University Press, Section B1.4.


V. William Porto, "Neural-Evolutionary Systems", 1997, in Handbook of Evolutionary Computation, T. Back, D.B. Fogel, Z. Michalewicz eds., Oxford, U.K.: IOP Press and Oxford University Press, Section D1.


V. William Porto, "Neural-Evolutionary Systems", 1997, Handbook of Neural Computation, E. Fiesler and R. Beale, eds., Oxford, U.K.: IOP Press and Oxford University Press, Section D2.


Fogel, L.J., Porto, V.W., and Owen, M., 1996, "An Intelligently Interactive Non-Rule-Based Computer Generated Force", Proceedings of the 6th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL: Institute for Simulation and Training, STRICOM-DMSO, pp. 265-270.


V. William Porto, 1995, "Non-Acoustic Sensor Array Localization using Evolutionary Programming", Evolutionary Programming IV: Proc. of the 4th Annual Conference on Evolutionary Programming, John R. McDonnell, Robert G. Reynolds, and David B. Fogel, eds., Cambridge, MA, The MIT Press, pp. 19-32.


V.W. Porto, D.B. Fogel, and L.J. Fogel, 1995, "Alternative Neural Network Training Methods", IEEE Expert, June 1995, Vol 10, No. 3, pp. 16-22.


V.W. Porto, 1994, "Array Localization using Least Squares Minimization", Proceedings of Oceans'94, Piscataway, NJ: IEEE Press, Vol II, pp. 527-532.


V.W. Porto, 1993, "A method for optimal step size determination for training neural networks", San Diego, CA, ORINCON Internal Technical Report, TR93-144.


V.W. Porto, 1992, "Data Fusion & Neural Network Applications", First Annual Deployable Surveillance Systems Technology Review, Naval Air Warfare Center Aircraft Division, April 1992, Warminster, PA: NAWC. (classified)


V.W. Porto and D.B. Fogel, 1992, "Neural Networks for AUV Guidance Control", Sea Technology, Feb. 1992, Vol 33, No. 2, pp. 25-35.


V.W. Porto, 1992, "Alternative Methods for Training Neural Networks", 1st Annual Conf. on Evolutionary Programming, David B. Fogel and Wirt Atmar, eds., La Jolla, CA: Evolutionary Programming Society, pp. 100-110.


V.W. Porto, 1990, "Evolutionary Methods for Training Neural Networks for Underwater Pattern Classification", 24th Annual Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 1990, Piscataway, NJ: IEEE Press, pp. 1015-1019.


V.W. Porto and D.B. Fogel, 1990, "Neural Network Techniques for Navigation of AUVs", Proc. of the Symposium on Autonomous Underwater Vehicle Technology, Wash. D.C, June 1990, Piscataway, NJ: IEEE Press, pp. 137-141.


D.B. Fogel, L.J. Fogel, and V.W. Porto, 1990, "Evolutionary Programming for Training Neural Networks", IJCNN Proceedings, Piscataway, NJ: IEEE Press, Vol. 1, pp. 601-605.


V.W. Porto, D.B. Fogel, and L.J. Fogel, 1990, "Evolving Neural Networks", Biological Cybernetics, Vol 63, pp. 487-493.


V.W. Porto, 1989, "Detection of Undersea Objects using Neural Networks", 23rd Annual Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 1989, Piscataway, NJ: IEEE Press, pp. 376-380.


V.W. Porto, 1988,"Neural Network Applications in Transient Detection and Classification", UnderSeas Defense Conference, San Diego, Oct. 1988. (classified)


V.W. Porto, 1988, "Transient Detection using Neural Networks and Artificial Intelligence", Proc. of the Submarine Technology Symposium, JHU/APL, June 1988. (classified)


Brett D. Castille and Vincent W. Porto, 1988, "Estimation of Size and Location of Buried Objects using Measurements Made with an Array of Magnetometers", San Diego, CA, ORINCON Internal Technical Report, OCR 88-U-0-114.


Daniel L. Alspach and Vincent W. Porto, 1985, "Containment Probabilities for APT One Array Initialization SPA", San Diego, CA, ORINCON Technical Report, TM 349.


Bill Porto and Gerry Anderson, 1985, "RELNAV Source Selection and Grid Acquisition on Initialization", San Diego, CA, ORINCON Technical Report, TM 369.


Bill Porto, 1984, "RELNAV Performance Spec. under Poor Geometry", San Diego, CA, ORINCON Technical Report, TM 346.


Fogel DB, Wasson EC, Boughton EM, Porto VW, and Shively J (1997) "Initial Results of Training Neural Networks to Detect Breast Cancer using Evolutionary Programming," Control and Cybernetics, vol. 26:3, pp. 497-510.


Fogel DB, Wasson EC, Boughton EM, and Porto VW (1997) "A Step Toward Computer-Assisted Mammography using Evolutionary Programming and Neural Networks," Cancer Letters, Vol. 119, pp. 93-97.


Fogel DB, Wasson EC, Boughton EM, and Porto VW (1997) "Linear and Neural Models for Classifying Breast Cancer," IEEE Trans. Medical Imaging.


Fogel, DB, Wasson EC, Boughton EM, and Porto VW (1997) "Evolving Artificial Neural Networks for Screening Features from Mammograms," Artificial Intelligence in Medicine.


Porto VW and Fogel DB (1997) "Evolving Neural Networks," In Artificial Neural Networks: Prospects for Medicine, R. Dybowski (ed.), Lands and Springer-Verlag, Berlin.


Fogel DB, Fogel LJ, and Porto VW (1991) "Evolutionary Methods for Training Neural Networks," Proc. of Conf. on Neural Networks for Ocean Engineering, Wash. DC, pp. 317-328.


Fogel DB and Ghozeil A (1998) "The schema theorem and the misallocation of trials in the presence of stochastic effects," Evolutionary Programming VII: Proc. of the 7th Ann. Conf. on Evolutionary Programming, V.W. Porto, N. Saravanan, D.E. Waagen, and A.E. Eiben (eds.), Springer, Berlin.


Fogel GB, Chellapilla K, and Fogel DB (1998) "Reconstruction of DNA sequence information from a simulated DNA chip using evolutionary programming," Evolutionary Programming VII: Proc. of the 7th Ann. Conf. on Evolutionary Programming, V.W. Porto, N. Saravanan, D.E. Waagen, and A.E. Eiben (eds.), Springer, Berlin.


Fogel DB, Angeline PJ, Porto VW, Wasson EC, and Boughton EM (1998) "Using Evolutionary Computation to Learn About Detecting Breast Cancer," 1998 IEEE International Conference on Systems, Man and Cybernetics: Data Mining and Knowledge Discovery, S.H. Rubin (chair).


Fogel GB, Porto VW, Weekes DG, Fogel DB, Griffey RH, McNeil JA, Lesnik E, Ecker DJ, Sampath R (2002) "Discovery of RNA Structural Elements Using Evolutionary Computation," Nucleic Acids Research. Vol. 30, pp 5310-5317.